Selected publications and conference contributions involving HySpex data


YearPublication Title authors publisher tags abstract keywords
YearPublication Title authors publisher tags abstract keywords
2017
Phenoliner: A New Field Phenotyping Platform for Grapevine Research,

MDPI Sensors 2017, 17, 1625; doi:10.3390/s17071625

Phenoliner: A New Field Phenotyping Platform for Grapevine Research Anna Kicherer, Katja Herzog, Nele Bendel, Hans-Christian Klück, Andreas Backhaus, Markus Wieland, Johann Christian Rose, Lasse Klingbeil, Thomas Läbe, Christian Hohl, Willi Petry, Heiner Kuhlmann, Udo Seiffert, Reinhard Töpfer MDPI Sensors 2017, 17, 1625; doi:10.3390/s17071625 In grapevine research the acquisition of phenotypic data is largely restricted to the field due to its perennial nature and size. The methodologies used to assess morphological traits and phenology are mainly limited to visual scoring. Some measurements for biotic and abiotic stress, as well as for quality assessments, are done by invasive measures. The new evolving sensor technologies provide the opportunity to perform non-destructive evaluations of phenotypic traits using different field phenotyping platforms. One of the biggest technical challenges for field phenotyping of grapevines are the varying light conditions and the background. In the present study the Phenoliner is presented, which represents a novel type of a robust field phenotyping platform. The vehicle is based on a grape harvester following the concept of a moveable tunnel. The tunnel it is equipped with different sensor systems (RGB and NIR camera system, hyperspectral camera, RTK-GPS, orientation sensor) and an artificial broadband light source. It is independent from external light conditions and in combination with artificial background, the Phenoliner enables standardised acquisition of high-quality, geo-referenced sensor data.
2017
Exploration applications of laboratory, field, and airborne imaging spectrometer data collected from copper porphyry deposits,

Sessão temática (Thematic Session): Sensoriamento Remoto Geológico (Geological Remote Sensing, XVIII Simpósio Brasileiro de Sensoriamento Remoto (SBSR),Tuesday, May 30, 2017

Exploration applications of laboratory, field, and airborne imaging spectrometer data collected from copper porphyry deposits Raymond Kokaly Sessão temática (Thematic Session): Sensoriamento Remoto Geológico (Geological Remote Sensing, XVIII Simpósio Brasileiro de Sensoriamento Remoto (SBSR),Tuesday, May 30, 2017
2017
A spectral analysis of multiple scattering effects in close range hyperspectral imagery of vegetation scenes: Application to nitrogen content assessment,

ICNIRS 2017 Denmark

A spectral analysis of multiple scattering effects in close range hyperspectral imagery of vegetation scenes: Application to nitrogen content assessment Nathalie Al Makdessi, Gilles Rabatel, Martin Ecarnot, Pierre Roumet ICNIRS 2017 Denmark
2017
Reflectance Spectroscopy Characteristics of Turquoise,

Minerals 2017, 7, 3; doi:10.3390/min7010003

Reflectance Spectroscopy Characteristics of Turquoise Jun-Ting Qiu, Hui Qi, Ji-Lin Duan Minerals 2017, 7, 3; doi:10.3390/min7010003 In this study, we determined the reflectance spectra of four types of turquoise with different hardness (porcelain, hard turquoise, soft turquoise, and loose turquoise) using an ASDTM TerraSpec spectrometer (spectral range 350–2500 nm, Visible-Near Infrared, and Short-wave Infrared). Several absorption features, including six narrow absorption peaks at 425 nm, 1480 nm, 2160 nm, 2218 nm, 2253 nm, and 2347 nm, and three wide peaks between 625–756 nm, 756–915 nm, and 1885–2133 nm have been identified. The strength of the absorption of turquoise increased with decreasing hardness. The absorption peaks at 2160 nm, 2218 nm, 2253 nm, 2347 nm, and 1885–2133 nm on some turquoise spectra (porcelain spectra, for example) were relatively weak, while those at 425 nm, 1480 nm, 625–756 nm, and 756–915 nm were always observed on all turquoise spectra, which could be the diagnostic absorption features for turquoise. Additionally, the hyper-spectral imaging (spectral range 1000–2500 nm, Short-wave Infrared) of the four types of turquoise were obtained using a HySpexTM imager. The Spectral Angle Mapper (SAM) method was successfully used to recognize turquoises, suggesting that hyper-spectral imaging may serve as a useful tool for fast turquoise identification and separation, especially for massive turquoise samples
2017
Hyperspectral remote sensing of coral reefs by semi-analytical model inversion – Comparison of different inversion setups,

Remote Sensing of Environment 190:348-365

Hyperspectral remote sensing of coral reefs by semi-analytical model inversion – Comparison of different inversion setups Tristan Petit, Touria Bajjouk, Pascal Mouquet, Christophe Delacourt Remote Sensing of Environment 190:348-365 Due to its high spectral and spatial resolutions, airborne hyperspectral imaging has great potential for becoming a powerful large-scale monitoring tool for coral reef communities. In recent years, methods based on radiative transfer model inversion have shown promising results for extracting information about seabed type, bottom depth and water constituents from hyperspectral imagery. However, low signal-to-noise ratios (SNR) due to low water-leaving radiance combined with environmental variability make it very difficult to design an optimal processing algorithm. Here, we selected a state-of-the-art, forward semi-analytical model in which we included a mixing model of four seabed albedo, namely sand, corals, algae and seagrass. The purpose of this paper was then to compare different setups of the inversion scheme, each one having its own theoretical strengths and weaknesses regarding the different confounding factors. Six inversion setups were implemented, corresponding to the combinations between (i) three cost functions: least square (LS), spectral angle mapper (SAM) and least square on spectral derivative (LSD), and (ii) two physical constraints imposed on the seabed type retrieval: abundance sum-to-one constraint (ASC) and a relaxed version (RASC). Performances of bathymetry and seabed type retrieval were evaluated on hyperspectral data acquired in a coral reef environment in Réunion Island. Our results showed that the accuracy and robustness of the bathymetric estimation were greatly influenced by the choice of the inversion setup. RASC-LSD produced the overall best performances even if SAM-based inversion setups showed particularly low error dispersion with respect to Lidar derived bathymetry. RASC-LSD also produced the most accurate results in terms of spatial coverage of benthic components on a very shallow area (inner part of a fringing reef). The results on our study areas clearly highlighted the interest of relaxing the ASC when the bottom depth is shallow. In deeper areas, ASC versions of LS- and LSD-based inversion setups produced the best seabed type mapping results. Only broad seabed types could be retrieved in areas deeper than 10 m.
2017
Alteration mapping on drill cores using a HySpex SWIR-320m hyperspectral camera: Application to the exploration of an unconformity-related uranium deposit (Saskatchewan, Canada),

Journal of Geochemical Exploration, Volume 172, January 2017, Pages 71-88, doi:http://dx.doi.org/10.1016/j.gexplo.2016.09.008

Alteration mapping on drill cores using a HySpex SWIR-320m hyperspectral camera: Application to the exploration of an unconformity-related uranium deposit (Saskatchewan, Canada) Magali Mathieu, Régis Roy, Patrick Launeau, Michel Cathelineau, David Quirt Journal of Geochemical Exploration, Volume 172, January 2017, Pages 71-88, doi:http://dx.doi.org/10.1016/j.gexplo.2016.09.008 In mineral exploration, the search for geophysical, geochemical, and mineralogical pathfinders is of critical importance, and many techniques have been used to detect the presence of mineralization and related host-rock alteration. In the case of unconformity-type uranium deposits that are spatially-linked to unconformities between sedimentary basin and underlying basement rocks, hydrothermal fluid-rock interactions produced extended alteration envelopes which are used to target mineralization and are therefore important guides for uranium exploration. The purpose of this study is to evaluate the utility of hyperspectral mapping of alteration minerals in drill core samples using the HySpex SWIR-320m hyperspectral camera that covers the 1300–2500 nm (SWIR) spectral range. A series of representative samples, including pegmatite, pelitic gneiss, and sandstone, from the area around the Cigar Lake uranium deposit (Athabasca Basin, Saskatchewan, Canada) were analyzed by SWIR reflectance spectroscopy and optical microscopy. An algorithm was developed and implemented in the IDL language to determine both the positions and depth of diagnostic absorption bands of various minerals, and to calculate semi-quantitative estimates of mineral content. Subsequent petrographic analysis using optical microscopy validated the hyperspectral mapping methodology. Selected alteration minerals present in the core samples, such as clay minerals and carbonates, were mapped. The “pseudo-modal” mineralogical composition for each sample was determined. The mineral maps highlight the mineralogy and the main petrographic textures such as foliation, bedding, veins, and the geometry of pervasive alteration. This study offers new perspectives for the use of this method in mineralogical analysis of drill core samples and the characterization of hydrothermal alteration. The proposed mineralogical semi-quantification methodology may be used in other geological contexts and should improve the understanding of the mineralogical alteration distribution around hydrothermal metal deposits.
2016
Airborne mapping of shallow water bathymetry in the optically complex waters of the Baltic Sea,

J. Appl. Remote Sens. 10(2), 025012 (May 09, 2016)

Airborne mapping of shallow water bathymetry in the optically complex waters of the Baltic Sea Ele Vahtmäe, Tiit Kutser J. Appl. Remote Sens. 10(2), 025012 (May 09, 2016) Accurate determination of the water depth is important for marine spatial planning, producing maritime charts for navigation, seabed morphology studies, and carrying out different activities in the coastal waters. Bathymetric data are lacking foremost in the shallow water regions as those areas are often inaccessible to the hydrographic ships carrying out echo sounding measurements. Remote sensing technology can be used as an alternative for shallow water bathymetry mapping. Varieties of empirical methods have been proposed for bathymetry retrieval, where the relationship between remotely sensed radiance of the water body and the water depth at sampled locations was established empirically. Two most widely used depth derivation methods, the linear band model proposed by Lyzenga (1978, 1985, 2006), and the log-transformed band ratio model proposed by Stumpf et al. (2003), were applied to the different preprocessing level airborne Hyspex hyperspectral images from the optically complex Baltic Sea area and evaluated for accuracy. Results showed that the Lyzenga linear band model outperformed the Stumpf log-transformed band ratio model. The best results were achieved with the atmospherically corrected images. The application of glint correction did not improve, but even reduced the accuracy of bathymetric maps.
2016
Vegetation Indices for Mapping Canopy Foliar Nitrogen in a Mixed Temperate Forest,

Remote Sens. 2016,8, 491; doi:10.3390/rs8060491

Vegetation Indices for Mapping Canopy Foliar Nitrogen in a Mixed Temperate Forest Zhihui Wang, Tiejun Wang, Roshanak Darvishzadeh, John W. Hearne Remote Sens. 2016,8, 491; doi:10.3390/rs8060491 Hyperspectral remote sensing serves as an effective tool for estimating foliar nitrogen using a variety of techniques. Vegetation indices (VIs) are a simple means of retrieving foliar nitrogen. Despite their popularity, few studies have been conducted to examine the utility of VIs for mapping canopy foliar nitrogen in a mixed forest context. In this study, we assessed the performance of 32 vegetation indices derived from HySpex airborne hyperspectral images for estimating canopy mass-based foliar nitrogen concentration (%N) in the Bavarian Forest National Park. The partial least squares regression (PLSR) was performed for comparison. These vegetation indices were classified into three categories that are mostly correlated to nitrogen, chlorophyll, and structural properties such as leaf area index (LAI). %N was destructively measured in 26 broadleaf, needle leaf, and mixed stand plots to represent the different species and canopy structure. The canopy foliar %N is defined as the plot-level mean foliar %N of all species weighted by species canopy foliar mass fraction. Our results showed that the variance of canopy foliar %N is mainly explained by functional type and species composition. The normalized difference nitrogen index (NDNI) produced the most accurate estimation of %N (R 2 CV = 0.79, RMSE CV = 0.26). A comparable estimation of %N was obtained by the chlorophyll index Boochs2 (R 2 CV = 0.76, RMSE CV = 0.27). In addition, the mean NIR reflectance (800–850 nm), representing canopy structural properties, also achieved a good accuracy in %N estimation (R 2 CV = 0.73, RMSE CV = 0.30). The PLSR model provided a less accurate estimation of %N (R 2 CV = 0.69, RMSE CV = 0.32). We argue that the good performance of all three categories of vegetation indices in %N estimation can be attributed to the synergy among plant traits (i.e., canopy structure, leaf chemical and optical properties) while these traits may converge across plant species for evolutionary reasons. Our findings demonstrated the feasibility of using hyperspectral vegetation indices to estimate %N in a mixed temperate forest which may relate to the effect of the physical basis of nitrogen absorption features on canopy reflectance, or the biological links between nitrogen, chlorophyll, and canopy structure. Vegetation Indices for Mapping Canopy Foliar Nitrogen in a Mixed Temperate Forest (PDF Download Available). Available from: https://www.researchgate.net/publication/303896088_Vegetation_Indices_for_Mapping_Canopy_Foliar_Nitrogen_in_a_Mixed_Temperate_Forest [accessed Jul 3, 2017].
2016
Hyperspectral Remote Sensing Of Wild Oyster Reefs,

Estuarine, Coastal and Shelf Science 172 (2016) 1-12

Hyperspectral Remote Sensing Of Wild Oyster Reefs Anthony Le Bris, Philippe Rosa, Astrid Lerouxel, Barillé Laurent Estuarine, Coastal and Shelf Science 172 (2016) 1-12 The invasion of the wild oyster Crassostrea gigas along the western European Atlantic coast has generatedchanges in the structure and functioning of intertidal ecosystems. Considered as an invasive species and atrophic competitor of the cultivated conspecific oyster, it is now seen as a resource by oyster farmersfollowing recurrent mass summer mortalities of oyster spat since 2008. Spatial distribution maps of wildoyster reefs are required by local authorities to help define management strategies. In this work, visible-near infrared (VNIR) hyperspectral and multispectral remote sensing was investigated to map twocontrasted intertidal reef structures: clusters of vertical oysters building three-dimensional dense reefs inmuddy areas and oysters growing horizontally creating large flat reefs in rocky areas. A spectral library,collected in situ for various conditions with an ASD spectroradiometer, was used to run Spectral AngleMapper classifications on airborne data obtained with an HySpex sensor (160 spectral bands) and SPOTsatellite HRG multispectral data (3 spectral bands). With HySpex spectral/spatial resolution, horizontaloysters in the rocky area were correctly classified but the detection was less efficient for vertical oystersin muddy areas. Poor results were obtained with the multispectral image and from spatially or spectrallydegraded HySpex data, it was clear that the spectral resolution was more important than the spatialresolution. In fact, there was a systematic mud deposition on shells of vertical oyster reefs explaining themisclassification of 30% of pixels recognized as mud or microphytobenthos. Spatial distribution maps ofoyster reefs were coupled with in situ biomass measurements to illustrate the interest of a remotesensing product to provide stock estimations of wild oyster reefs to be exploited by oyster producers.This work highlights the interest of developing remote sensing techniques for aquaculture applications incoastal areas Hyperspectral Remote Sensing Of Wild Oyster Reefs (PDF Download Available). Available from: https://www.researchgate.net/publication/292210440_Hyperspectral_Remote_Sensing_Of_Wild_Oyster_Reefs [accessed Jul 3, 2017].
2016
GeoMAP-Trans - a processing chain for geocorrected at-surface reflectance retrieval for translational laboratory scans,

EARSeL Symposium, Bonn, Germany, June 20 – 24, 2016

GeoMAP-Trans - a processing chain for geocorrected at-surface reflectance retrieval for translational laboratory scans Christian Rogass, Maximilian Brell, Christian Mielke, Nina Kristine Boesche EARSeL Symposium, Bonn, Germany, June 20 – 24, 2016
2016
Single seed near-infrared hyperspectral imaging in determining tomato (Solanum lycopersicum L.) seed quality in association with multivariate data analysis,

Sensors and Actuators B: Chemical; Volume 237, December 2016, Pages 1027-1034

Single seed near-infrared hyperspectral imaging in determining tomato (Solanum lycopersicum L.) seed quality in association with multivariate data analysis Santosh Shrestha, Matej Knapič, Uroš Žibrat, Lise Christina Deleuran, René Gislum Sensors and Actuators B: Chemical; Volume 237, December 2016, Pages 1027-1034 Near-infrared (NIR) hyperspectral imaging was explored as a rapid and non-destructive method of investigating seed quality parameters such as seed viability and variation in tomato seed lots. The seed lots differed with year of production and variety. Four tomato varieties: Cal J, Monprecus, NCL and Chiuri from 2013, 2014 and 2015 were used in the study. The extracted NIR hyperspectral data from 975 to 2500 nm were analysed by principal component analysis (PCA) and partial least squares- discriminant analysis (PLS-DA). No distinct patterns of separation between viable and non-viable tomato seeds were revealed by the PCA. Our findings showed a pattern of separation in the tomato seed lots due to production years and varieties. The PLS-DA showed the ability to predict with ∼100 percent accuracy for varietal class membership when only the seeds of a single harvest year were included in the model. The accuracy from PLS-DA on pooled samples (all seeds from all varieties) predicted varietal class membership in the range from 34 to 88 percent. High variation in the seed lots could have caused high variation in the predicted varietal class membership. The NIR regions with chemical information from Csingle bondH, Nsingle bondH and Osingle bondH had influence on the PCA and PLS-DA models. The study presents the prospects of using NIR hyperspectral imaging in varietal identification studies of tomato seeds though we recommend a thorough validation of models.
2016
Multifractal analysis for multivariate data with application to remote sensing,

UNIVERSITÉ DE TOULOUSE

Multifractal analysis for multivariate data with application to remote sensing Sébastien COMBREXELLE UNIVERSITÉ DE TOULOUSE Texture characterization is a central element in many image processing applications. Texture analysis can be embedded in the mathematical framework of multifractal analysis, enabling the study of the fluctuations in regularity of image intensity and providing practical tools for their assessment, the wavelet coefficients or wavelet leaders. Although successfully applied in various contexts, multifractal analysis suffers at present from two major limitations. First, the accurate estimation of multifractal parameters for image texture remains a challenge, notably for small image sizes. Second, multifractal analysis has so far been limited to the analysis of a single image, while the data available in applications are increasingly multivariate. The main goal of this thesis is to develop practical contributions to overcome these limitations. The first limitation is tackled by introducing a generic statistical model for the logarithm of wavelet leaders, parametrized by multifractal parameters of interest. This statistical model enables us to counterbalance the variability induced by small sample sizes and to embed the estimation in a Bayesian framework. This yields robust and accurate estimation procedures, effective both for small and large images. The multifractal analysis of multivariate images is then addressed by generalizing this Bayesian framework to hierarchical models able to account for the assumption that multifractal properties evolve smoothly in the dataset. This is achieved via the design of suitable priors relating the dynamical properties of the multifractal parameters of the different components composing the dataset. Different priors are investigated and compared in this thesis by means of numerical simulations conducted on synthetic multivariate multifractal images. This work is further completed by the investigation of the potential benefits of multifractal analysis and the proposed Bayesian methodology for remote sensing via the example of hyperspectral imaging.
2016
A REVIEW OF HYPERSPECTRAL IMAGING IN CLOSE RANGE APPLICATIONS,

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLI-B5, 2016 XXIII ISPRS Congress, 12–19 July 2016, Prague, Czech Republic

A REVIEW OF HYPERSPECTRAL IMAGING IN CLOSE RANGE APPLICATIONS T.H. Kurz, S.J. Buckley The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLI-B5, 2016 XXIII ISPRS Congress, 12–19 July 2016, Prague, Czech Republic Hyperspectral imaging is an established method for material mapping, which has been conventionally applied from airborne and spaceborne platforms for a range of applications, including mineral and vegetation mapping, change detection and environmental studies. The main advantage of lightweight hyperspectral imagers lies in the flexibility to deploy them from various platforms (terrestrial imaging and from unmanned aerial vehicles; UAVs), as well as the high spectral resolution to cover an expanding wavelength range. In addition, spatial resolution allows object sampling distances from micrometres to tens of centimetres – complementary to conventional nadir-looking systems. When this new type of imaging device was initially released, few instruments were available and the applicability and potential of the method was restricted. Today, a wider range of instruments, with a range of specifications, is available, with significant improvements over the first generation of technology. In this contribution, the state-ofthe-art of hyperspectral imaging will be reviewed from a close range measurement perspective, highlighting how the method supplements geometric modelling techniques. An overview of the processing workflow, adjusted to the more complex close range imaging scenario will be given. This includes the integration with 3D laser scanning and photogrammetric models to provide a geometric framework and real world coordinate system for the hyperspectral imagery.
2016
Integration of Auxiliary Data Knowledge in Prototype Based Vector Quantization and Classification Models,

Der Fakultät für Mathematik und Informatik, University Leipzig

Integration of Auxiliary Data Knowledge in Prototype Based Vector Quantization and Classification Models Marika Kaden Der Fakultät für Mathematik und Informatik, University Leipzig
2016
HySpex Hyperspectral Mineral Mapping of Asiha Gold Ore District in Dulan County,Qinghai Province and Its Prospecting Implications,

Acta Geologica Sinica 2015-01

HySpex Hyperspectral Mineral Mapping of Asiha Gold Ore District in Dulan County,Qinghai Province and Its Prospecting Implications Yu Sun, Yingjun Zhao, Hanbo Li, Donghua Lu, Feng Tian, Kai Qin, Guofang Yang, Jiajing Zhou, Pengfei Liu Acta Geologica Sinica 2015-01 The ground-based imaging hyperspectral remote sensing,having an advantage of integrated image and spectrum,is a frontier direction in the remote sensing field,and it can be applied to directly identifying surface objects based on spectral characteristics.This study took the imaging hyperspectral data for alteration belts in the Asiha gold ore district of Dulan county as an example,established a standard data processing workflow,in which the flat field method based on statistical models was applied to reconstruct spectrum,and the end member selection based on expert knowledge was utilized for mineral mapping using MTMF method.Based on above,true color images at a scale of 1∶100 and distribution of five hyperspectral surface objects(limonite,muscovite,etc.)were mapped.It is concluded that the typical alteration minerals in this ore district are limonite and muscovite,and ideal results are achieved after field verification using ASD spectral measurements.It is suggested that the ground-based imaging hyperspectral data have good application results and show a promising potential in geology.
2016
Application of HySpex Hyperspectral Image in Analyse Trees on Urban Areas: Tree Species Identification and Monitoring of Tree Damages,

36th EARSeL Symposium 2016: Frontiers in Earth Observation

Application of HySpex Hyperspectral Image in Analyse Trees on Urban Areas: Tree Species Identification and Monitoring of Tree Damages Anna Jarocinska, Anna Robak, Dominik Kopec, Bogdan Zagajewski, Jan Niedzielko, Jan Ochtyra, Lukasz Slawik, Adriana Marcinkowska-Ochtyra, Joanna Walesiak, Prakash Madhav Nimbalkar 36th EARSeL Symposium 2016: Frontiers in Earth Observation Urban vegetation is an important part of the city. It is changing the microclimate in the city, provides a great amount of oxygen and isolates from the dust and the noise. It is also exposed to stress caused by many factors like air pollution, higher temperatures, especially in the summer, strong winds and soil salinisation during winter. Because of that it is important to develop a method to monitor the plant communities and to monitor the state of the plants. The aim was assessment of the possibility to use hyperspectral HySpex data to analyze trees in the city. The analyses were conducted in Bialystok city in North-East Poland. The data were used to detect dominant tree species and to analyze the biophysical parameters of trees: discoloration and defoliation and to discover the changes caused by drought. Firstly, the hyperspectral image was acquired by MGGP Aero aircraft on 3rd July and during the drought on 27th of August 2015 using HySpex scanners (with 451 spectral bands from VNIR 400-1000 nm and SWIR 930-2500 nm) with spatial resolution 0.5 in VNIR and 1 m in SWIR. In the same time field measurements were done – 233 polygons with tree species and values of discoloration and defoliation. The same trees were measured in July and August. Also was acquired reference spectrum using ASD FieldSpec 4 for object spectrally stable and flat like concrete, asphalt, sand and water. ALS data was collected from The National Geodetic and Cartographic Resources. On the basis of 12 point/meter point cloud the digital surface model was generated with cell size of 0.5 meter. Hyspex images were ortho-rectified using flight parameters and digital surface model. Parametric geocoding was performed in PARGE software. Imagery from both VNIR and SWIR sensors was resampled to 1 m spatial resolution and combined into one cube. Atmospheric correction was done using ATCOR4 software and assessed with ground spectral reflectance measurement. Mask for trees was created using height for the object based on ALS data and NDVI calculated from HySpex images. Based on field measurements were created spectrally pure training pixels for each species. Next, Spectral Angle Mapper classification was performed. The accuracy was tested using reference data. The values of vegetation indices were calculated to find the correlation between image and biophysical parameters. From the image from 3rd July were acquired values of vegetation indices from the test polygons and were correlated with the values of discoloration and defoliation. Using estimated regression models the values of discoloration and defoliation were calculated for whole trees on the image. The accuracy was tested using RMSE values based on reference values of discoloration and defoliation. Using developed model the discoloration and defoliation was calculated for the image from 27th of August. The damages were verified based on field measurements. The last step was the analysis of the changes in damages between two dates.
2016
Monitoring biodiversity in cultural landscapes: development of remote sensing- and GIS-based methods,

Lund University, Faculty of Science, Department of Physical Geography and Ecosystem Science

Monitoring biodiversity in cultural landscapes: development of remote sensing- and GIS-based methods Jonas Dalmayne Lund University, Faculty of Science, Department of Physical Geography and Ecosystem Science In this thesis, I explore the relationships between structural and compositional landscape properties, and species diversity, using remotely sensed data on a variety of spatial scales. The thesis shows that increased landscape heterogeneity, measured using environmental and spectral variables that were used both separately and combined, is generally positively related to plant species richness. I further found that plant species richness could be predicted with
2016
Airborne Hyperspectral Data Predict Fine-Scale Plant Species Diversity in Grazed Dry Grasslands,

Remote Sens. 2016, 8, 133; doi:10.3390/rs8020133

Airborne Hyperspectral Data Predict Fine-Scale Plant Species Diversity in Grazed Dry Grasslands Thomas Möckel, Jonas Dalmayne, Barbara Schmid, Honor C. Prentice, Karin Hall Remote Sens. 2016, 8, 133; doi:10.3390/rs8020133 Semi-natural grasslands with grazing management are characterized by high fine-scale species richness and have a high conservation value. The fact that fine-scale surveys of grassland plant communities are time-consuming may limit the spatial extent of ground-based diversity surveys. Remote sensing tools have the potential to support field-based sampling and, if remote sensing data are able to identify grassland sites that are likely to support relatively higher or lower levels of species diversity, then field sampling efforts could be directed towards sites that are of potential conservation interest. In the present study, we examined whether aerial hyperspectral (414–2501 nm) remote sensing can be used to predict fine-scale plant species diversity (characterized as species richness and Simpson’s diversity) in dry grazed grasslands. Vascular plant species were recorded within 104 (4 m ˆ 4 m) plots on the island of Öland (Sweden) and each plot was characterized by a 245-waveband hyperspectral data set. We used two different modeling approaches to evaluate the ability of the airborne spectral measurements to predict within-plot species diversity: (1) a spectral response approach, based on reflectance information from (i) all wavebands, and (ii) a subset of wavebands, analyzed with a partial least squares regression model, and (2) a spectral heterogeneity approach, based on the mean distance to the spectral centroid in an ordinary least squares regression model. Species diversity was successfully predicted by the spectral response approach (with an error of ca. 20%) but not by the spectral heterogeneity approach. When using the spectral response approach, iterative selection of important wavebands for the prediction of the diversity measures simplified the model but did not improve its predictive quality (prediction error). Wavebands sensitive to plant pigment content (400–700 nm) and to vegetation structural properties, such as above-ground biomass (700–1300 nm), were identified as being the most important predictors of plant species diversity. We conclude that hyperspectral remote sensing technology is able to identify fine-scale variation in grassland diversity and has a potential use as a tool in surveys of grassland plant diversity.
2016
Quantitative remote sensing of forest leaf functional traits: Leaf dry matter content and specific leaf area,

University of Twente

Quantitative remote sensing of forest leaf functional traits: Leaf dry matter content and specific leaf area Abebe Mohammed Ali University of Twente
2016
HyLab: A hyperspectral laboratory for surface water and vegetation characterization in Alaska's Arctic and boreal regions,

The 14th International Circumpolar Remote Sensing Symposium September 12-16, 2016 Homer, Alaska

HyLab: A hyperspectral laboratory for surface water and vegetation characterization in Alaska's Arctic and boreal regions Anupma Prakash, Jordi Cristóbal, Marcel Buchhorn, Patrick Graham, Martin Stuefer The 14th International Circumpolar Remote Sensing Symposium September 12-16, 2016 Homer, Alaska
2016
Feasibility Study for Applying Spectral Imaging for Wheat Grain Authenticity Testing in Pasta,

Food and Nutrition Sciences, 2016, 7, 355-361

Feasibility Study for Applying Spectral Imaging for Wheat Grain Authenticity Testing in Pasta Timothy Wilkes, Gavin Nixon, Claire Bushell, Adrian Waltho, Amer Alroichdi, Malcolm Burns Food and Nutrition Sciences, 2016, 7, 355-361 Authentication of pasta is currently determined using molecular biology-based techniques focusing on DNA as the target analyte. Whilst proven to be effective, these approaches can be criticised as being destructive, time consuming, and requiring specialist instrument training. Advances in the field of multispectral imaging (MSI) and hyperspectral imaging (HSI) have facilitated the development of compact imaging platforms with the capability to rapidly differentiate a range of materials (inclusive of grains and seeds) based on surface colour, texture and chemical composition. This preliminary investigation evaluated the applicability of spectral imaging for identification and quantitation of durum wheat grain samples in relation to pasta authenticity. MSI and HSI were capable of rapidly distinguishing between durum wheat and adulterant common wheat cultivars and assigning percentage adulteration levels characterised by low biases and good repeatability estimates. The results demonstrated the potential for spectral imaging based seed/grain adulteration testing to augment existing standard molecular approaches for food authenticity testing.
2016
Characterizing Biophysical Properties of Forest Canopies with Hyperspectral Imaging Systems – Research Challenges and Perspectives,

EARSeL 3rd workshop SIG on forestry: Breaking Dimensions and Resolutions of Forest Remote Sensing Data

Characterizing Biophysical Properties of Forest Canopies with Hyperspectral Imaging Systems – Research Challenges and Perspectives Joachim Hill EARSeL 3rd workshop SIG on forestry: Breaking Dimensions and Resolutions of Forest Remote Sensing Data
2016
Hyperspectral Mineralogical and Lithological Mapping of Metasediments and Metavolcanics of Gamsberg, Aggeneys, South Africa,

GRSG 27th Annual Conference, London, 8th December 2016

Hyperspectral Mineralogical and Lithological Mapping of Metasediments and Metavolcanics of Gamsberg, Aggeneys, South Africa Martin C. Schodlok, Michaela Frei GRSG 27th Annual Conference, London, 8th December 2016
2016
A physically-based model for retrieving foliar biochemistry and leaf orientation using close-range imaging spectroscopy,

Remote Sensing of Environment 177 (2016) 220–236

A physically-based model for retrieving foliar biochemistry and leaf orientation using close-range imaging spectroscopy Sylvain Jay, Ryad Bendoula, Xavier Hadoux, Jean-Baptiste Féret, Nathalie Gorretta-Monteiro Remote Sensing of Environment 177 (2016) 220–236 Radiative transfer models have long been used to characterize the foliar content at the leaf and canopy levels. However, they still do not apply well to close-range imaging spectroscopy, especially because directional effects are usually not taken into account. For this purpose, we introduce a physical approach to describe and simulate the variation in leaf reflectance observed at this scale. Two parameters are thus introduced to represent (1) specular reflection at the leaf surface and (2) local leaf orientation. The model, called COSINE (ClOse-range Spectral ImagiNg of lEaves), can be coupled with a directional–hemispherical reflectance model of leaf optical properties to relate the measured reflectance to the foliar content. In this study, we show that, when combining COSINE with the PROSPECT model, the overall PROCOSINE model allows for a robust submillimeter retrieval of foliar content based on numerical inversion and pseudo-bidirectional reflectance factor hyperspectral measurements. The relevance of the added parameters is first shown through a sensitivity analysis performed in the visible and near-infrared (VNIR) and shortwave infrared (SWIR) ranges. PROCOSINE is then validated based on VNIR and SWIR hyperspectral images of various leaf species exhibiting different surface properties. Introducing these two parameters within the inversion allows us to obtain accurate maps of PROSPECT parameters, e.g., the chlorophyll content in the VNIR range, and the equivalent water thickness and leaf mass per area in the SWIR range. Through the estimation of light incident angle, the PROCOSINE inversion also provides information on leaf orientation, which is a critical parameter in vegetation remote sensing
2016
Retrieval of water quality algorithms from airborne HySpex camera for oxbow lakes in north-eastern Poland,

EGU General Assembly 2016, held 17-22 April, 2016 in Vienna Austria, p.14167

Retrieval of water quality algorithms from airborne HySpex camera for oxbow lakes in north-eastern Poland Malgorzata Slapinska, Tomasz Berezowski, Magdalena Frak, Jaroslaw Chormanski EGU General Assembly 2016, held 17-22 April, 2016 in Vienna Austria, p.14167 The aim of this study was to retrieve empirical formulas for water quality of oxbow lakes in Lower Biebrza Basin (river located in NE Poland) using HySpex airborne imaging spectrometer. Biebrza River is one of the biggest wetland in Europe. It is characterised by low contamination level and small human influence. Because of those characteristics Biebrza River can be treated as a reference area for other floodplains and fen ecosystem in Europe. Oxbow lakes are important part of Lower Biebrza Basin due to their retention and habitat function. Hyperspectral remote sensing data were acquired by the HySpex sensor (which covers the range of 400-2500 nm) on 01-02.08.2015 with the ground measurements campaign conducted 03-04.08.2015. The ground measurements consisted of two parts. First part included spectral reflectance sampling with spectroradiometer ASD FieldSpec 3, which covered the wavelength range of 350-2500 nm at 1 nm intervals. In situ data were collected both for water and for specific objects within the area. Second part of the campaign included water parameters such as Secchi disc depth (SDD), electric conductivity (EC), pH, temperature and phytoplankton. Measured reflectance enabled empirical line atmospheric correction which was conducted for the HySpex data. Our results indicated that proper atmospheric correction was very important for further data analysis. The empirical formulas for our water parameters were retrieved based on reflecatance data. This study confirmed applicability of HySpex camera to retrieve water quality.
2016
Airborne Imaging Spectrometer HySpex,

DLR Remote Sensing Technology Institute (IMF), Journal of large-scale research facilities, 2, A93 (2016) doi:http://dx.doi.org/10.17815/jlsrf-2-151

Airborne Imaging Spectrometer HySpex Claas Henning Köhler DLR Remote Sensing Technology Institute (IMF), Journal of large-scale research facilities, 2, A93 (2016) doi:http://dx.doi.org/10.17815/jlsrf-2-151 The Remote Sensing Technology Institute (IMF) of the German Aerospace Center (DLR) operates an airborne imaging spectrometer system called HySpex. Owing to its accurate calibration, the system is well suited for benchmark reference measurements and feasibility studies for Earth observation applications. The sensor also serves as simulator for the upcoming German satellite mission EnMAP. HySpex covers the spectral range from the visible and near infrared (VNIR) to the short wave infrared (SWIR) and it has been extensively characterised with numerous measurements in the IMF calibration laboratory (CHB). The HySpex instrument is made available to interested third party users through the user service Optical Airborne Remote Sensing and Calibration Homebase (OpAiRS).
2016
Towards automated sorting of Atlantic cod (Gadus morhua) roe, milt, and liver - Spectral characterization and classification using visible and near-infrared hyperspectral imaging,

Food Control 62, 337-345

Towards automated sorting of Atlantic cod (Gadus morhua) roe, milt, and liver - Spectral characterization and classification using visible and near-infrared hyperspectral imaging Lukasz A. Paluchowski, E. Misimi, Lise Randeberg Food Control 62, 337-345 Technological solutions regarding automated sorting of food according to their quality parameters are of great interest to food industry. In this regard, automated sorting of fish rest raw materials remains as one of the key challenges for the whitefish industry. Currently, the sorting of roe, milt, and liver in whitefish fisheries is done manually. Automated sorting could enable higher profitability, flexibility in production and increase the potential for high value products from roe, milt and liver that can be used for human consumption. In this study, we investigate and present a solution for classification of Atlantic cod (Gadus morhua) roe, milt and liver using visible and near-infrared hyperspectral imaging. Recognition and classification of roe, milt and liver from fractions is a prerequisite to enabling automated sorting. Hyperspectral images of cod roe, milt and liver samples were acquired in the 400-2500 nm range and specific absorption peaks were characterized. Inter- and intra-variation of the materials were calculated using spectral similarity measure. Classification models operating on one and two optimal spectral bands were developed and compared to the classification model operating on the full VIS/NIR (400-1000 nm) range. Classification sensitivity of 70% and specificity of 94% for one-band model, and 96% and 98% for two-band model (sensitivity and specificity respectively) were achieved. Generated classification maps showed that sufficient discrimination between cod liver, roe and milt can be achieved using two optimal wavelengths. Classification between roe, milt and liver is the first step towards automated sorting.
2015
DRILL CORE MINERAL ANALYSIS BY MEANS OF THE HYPERSPECTRAL IMAGING SPECTROMETER HySpex, XRD AND ASD IN PROXIMITY OF THE MÝTINA MAAR, CZECH REPUBLIC,

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-1/W5, 2015 International Conference on Sensors & Models in Remote Sensing & Photogrammetry, 23–25 Nov 2015, Kish Island, Iran

DRILL CORE MINERAL ANALYSIS BY MEANS OF THE HYPERSPECTRAL IMAGING SPECTROMETER HySpex, XRD AND ASD IN PROXIMITY OF THE MÝTINA MAAR, CZECH REPUBLIC Friederike Koerting, Christian Rogass, Horst Kaempf, Christin Lubitz, Ulrich Harms, Michael Schudack, Raymond Kokaly, Christian Mielke, Nina Kristine Boesche, Uwe Altenberger The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-1/W5, 2015 International Conference on Sensors & Models in Remote Sensing & Photogrammetry, 23–25 Nov 2015, Kish Island, Iran Imaging spectroscopy is increasingly used for surface mapping. Therefore different expert systems are being utilized to identify surface cover materials. Those expert systems mainly rely on the spectral comparison between unknown and library spectra, but their performances were only limited qualified. This study aims on the comparative analysis of drill core samples from the recently discovered maar system in the Czech Republic. Drill core samples from the surrounding area of the Mýtina maar were analyzed by X-Ray diffraction (XRD) and the hyperspectral spectrometer HySpex. Additionally, soil samples were measured in-situ by the ASD FieldSpec4 and in the laboratory by the HySpex VNIR/SWIR spectrometer system. The data was then analyzed by the MICA-algorithm and the results were compared to the results of the XRD-analysis. The XRD-analysis served here as validation basis. The results of the hyperspectral and the XRD analyses were used to densify a volcanic map that also integrates in-situ soil measurements in the surrounding area of Mýtina. The comparison of the XRD- and solaroptical remote sensing results showed a good correlation of qualified minerals if the soil organic carbon content was significantly low. Contrary to XRD, smectites and muscovites were also straightforward identified that underlines the overall performance of the approach to identify minerals. Basically, in this work an operable approach is proposed that enables the fast, repeatable and detailed analysis of drill cores, drill core samples and soil samples and, hence, provides a higher performance than state-of-the-art XRD-analyses.
2015
Vessel contrast enhancement in hyperspectral images,

SPIE BiOS, 93180G-93180G-10

Vessel contrast enhancement in hyperspectral images Asgeir Bjorgan, Martin Denstedt, Matija Milanic, Lukasz A. Paluchowski, Lise Randeberg SPIE BiOS, 93180G-93180G-10
2015
Hyperspectral imaging for detection of cholesterol in human skin,

SPIE BiOS, 93320W-93320W-12

Hyperspectral imaging for detection of cholesterol in human skin Matija Milanic, Asgeir Bjorgan, M. Larsson, P. Marraccini, T. Strömberg, Lise Randeberg SPIE BiOS, 93320W-93320W-12
2015
Detection of hypercholesterolemia using hyperspectral imaging of human skin,

European Conferences on Biomedical Optics, 95370C-95370C-11

Detection of hypercholesterolemia using hyperspectral imaging of human skin Matija Milanic, Asgeir Bjorgan, M. Larsson, T. Strömberg, Lise Randeberg European Conferences on Biomedical Optics, 95370C-95370C-11
2015
Towards real-time medical diagnostics using hyperspectral imaging technology,

European Conferences on Biomedical Optics, 953712-953712-9

Towards real-time medical diagnostics using hyperspectral imaging technology Asgeir Bjorgan, Lise Randeberg European Conferences on Biomedical Optics, 953712-953712-9
2015
Hyperspectral imaging for detection of arthritis: feasibility and prospects,

Journal of Biomedical Optics 20 (9), 096011-096011

Hyperspectral imaging for detection of arthritis: feasibility and prospects Matija Milanic, Lukasz A. Paluchowski, Lise Randeberg Journal of Biomedical Optics 20 (9), 096011-096011
2015
PROSPECT Inversions of Leaf Laboratory Imaging Spectroscopy — A Comparison of Spectral Range and Inversion Technique Influences,

Photogrammetrie — Fernerkundung — Geoinformatik, 2015 (3): 231-240. http://dx.doi.org/10.1127/pfg/2015/0264

PROSPECT Inversions of Leaf Laboratory Imaging Spectroscopy — A Comparison of Spectral Range and Inversion Technique Influences Henning Buddenbaum, Joachim Hill Photogrammetrie — Fernerkundung — Geoinformatik, 2015 (3): 231-240. http://dx.doi.org/10.1127/pfg/2015/0264
2015
Using VNIR and SWIR Field Imaging Spectroscopy for Drought Stress Monitoring of Beech Seedlings,

International Journal of Remote Sensing, 36 (18): 4590-4605. http://doi.org/10.1080/01431161.2015.1084435

Using VNIR and SWIR Field Imaging Spectroscopy for Drought Stress Monitoring of Beech Seedlings Henning Buddenbaum, O. Stern, B. Paschmionka, E. Hass, T. Gattung, Johannes Stoffels, Joachim Hill, W. Werner International Journal of Remote Sensing, 36 (18): 4590-4605. http://doi.org/10.1080/01431161.2015.1084435
2015
Spectral Scream: Hyperspectral image acquisition and analysis of a masterpiece,

Book Chapter in “Public paintings by Edvard Munch and some of his contemporaries. Changes and conservation challenges,” Archetype Publications, London, (2015)

Spectral Scream: Hyperspectral image acquisition and analysis of a masterpiece Jon Yngve Hardeberg, Sony George, Ferdinand Deger, Ivar Baarstad, Julio Ernesto Hernández Palacios Book Chapter in “Public paintings by Edvard Munch and some of his contemporaries. Changes and conservation challenges,” Archetype Publications, London, (2015)
2015
Color and hyperspectral image segmentation for historical documents,

Digital Heritage (September 2015)

Color and hyperspectral image segmentation for historical documents I. Ciortan, Hilda Deborah, Sony George, Jon Yngve Hardeberg Digital Heritage (September 2015)
2015
Ink classification and visualisation of historical manuscripts: Application of hyperspectral imaging,

13th International Conference on Document Analysis and Recognition (ICDAR 2015)

Ink classification and visualisation of historical manuscripts: Application of hyperspectral imaging Sony George, Jon Yngve Hardeberg 13th International Conference on Document Analysis and Recognition (ICDAR 2015)
2015
Hyperspectral crack detection in paintings,

Colour and Visual Computing Symposium (CVCS) (August 2015)

Hyperspectral crack detection in paintings Hilda Deborah, N. Richard, Jon Yngve Hardeberg Colour and Visual Computing Symposium (CVCS) (August 2015)
2015
A comprehensive evaluation of spectral distance functions and metrics for hyperspectral image processing,

Journal of Selected Topics in Applied Earth Observations and Remote Sensing, IEEE

A comprehensive evaluation of spectral distance functions and metrics for hyperspectral image processing Hilda Deborah, N. Richard, Jon Yngve Hardeberg Journal of Selected Topics in Applied Earth Observations and Remote Sensing, IEEE
2015
Vector crack detection for cultural heritage paintings,

Traitement et Analyse de l'Information Methodes et Applications (TAIMA)

Vector crack detection for cultural heritage paintings Hilda Deborah, N. Richard, Jon Yngve Hardeberg Traitement et Analyse de l'Information Methodes et Applications (TAIMA)
2015
Spectral ordering assessment using spectral median filters,

Mathematical Morphology and Its Applications to Signal and Image Processing, Lecture Notes in Computer Science, vol. 9082, pp. 387-397. Springer International Publishing

Spectral ordering assessment using spectral median filters Hilda Deborah, N. Richard, Jon Yngve Hardeberg Mathematical Morphology and Its Applications to Signal and Image Processing, Lecture Notes in Computer Science, vol. 9082, pp. 387-397. Springer International Publishing
2015
Spectral impulse noise model for spectral image processing,

Computational Color Imaging, Lecture Notes in Computer Science, vol. 9016. Springer International Publishing

Spectral impulse noise model for spectral image processing Hilda Deborah, N. Richard, Jon Yngve Hardeberg Computational Color Imaging, Lecture Notes in Computer Science, vol. 9016. Springer International Publishing
2015
A database for spectral image quality,

Image Quality and System Performance XII, San Francisco, CA, USA, February 2015, vol. 9396, p. 25, IS&T/SPIE

A database for spectral image quality Steven Le Moan, Sony George, Marius Pedersen, Jana Blahova, Jon Yngve Hardeberg Image Quality and System Performance XII, San Francisco, CA, USA, February 2015, vol. 9396, p. 25, IS&T/SPIE
2015
Mapping of iron and steelwork by-products using close range hyperspectral imaging: A case study in Thuringia, Germany,

European Journal of Remote Sensing, 48: 489-509. doi:10.5721/EuJRS20154828.

Mapping of iron and steelwork by-products using close range hyperspectral imaging: A case study in Thuringia, Germany Michael Denk, Cornelia Gläßer, Tobias H. Kurz, Simon J. Buckley, Peter Drissen European Journal of Remote Sensing, 48: 489-509. doi:10.5721/EuJRS20154828. This paper presents the first use of close range terrestrial hyperspectral imaging to explore by-products from the iron and steel industry at a dump site cross section, using established mapping approaches in geological remote sensing. Laboratory reflectance measurements, X-Ray diffraction and chemical analysis provided a benchmark for the imaging results. In addition, terrestrial laser scanning was applied to create a high resolution 3D model of the studied section, for hyperspectral image and classification integration. Results demonstrate the applicability of spectral methods for remote discrimination and mapping of materials from iron and steel production which are of potential economic interest. This will aid the appraisal of resource distribution for urban mining and material recycling. - See more at: http://www.aitjournal.com/articleView.aspx?ID=955#sthash.TGMzlKDb.dpuf
2015
REMOTE SENSING OF WILD OYSTER REEFS (CRASSOSTREA GIGAS) IN A SHELLFISH ECOSYSTEM,

Aquaculture, Nature and Society, October 2015,Rotterdam, Netherlands

REMOTE SENSING OF WILD OYSTER REEFS (CRASSOSTREA GIGAS) IN A SHELLFISH ECOSYSTEM A. Le Bris, P. Rosa, I. Benyoucef, B. Cognie, P. Gernez, M. Robin, Patrick Launeau, L. Barillé Aquaculture, Nature and Society, October 2015,Rotterdam, Netherlands The invasion of wild oyster Crassostrea gigas along the western European Atlantic coast generates changes in the structure and functioning of intertidal ecosystems (Le Berre et al., 2009). Initially considered as an invasive species, it is now seen as a resource by oyster farmers after the mass summer mortalities of cultivated oysters (European Food Safety Authority, 2010). Indeed, wild oysters are now collected both by recreational and professional fisherman but also by oyster producers to replenish their stock and this generates local conflicts. It is thus necessary to obtain spatial distribution maps of wild oysters to assess their stock and analyze their dynamic to define management strategies. In this study, spatial distribution of wild oysters was analyzed in Bourgneuf bay (France; 47°0'N, 2°10'W), an important shellfish production basin, using remote sensing.
2015
Hyperspectral REE (Rare Earth Element) Mapping of Outcrops - Applications for Neodymium Detection,

Remote Sensing 2015, 7(5), 5160-5186; doi:10.3390/rs70505160

Hyperspectral REE (Rare Earth Element) Mapping of Outcrops - Applications for Neodymium Detection Nina Kristine Boesche, Christian Rogass, Christin Lubitz, Maximilian Brell, Sabrina Herrmann, Christian Mielke, Sabine Tonn, Oona Appelt, Uwe Altenberger, Hermann Kaufmann Remote Sensing 2015, 7(5), 5160-5186; doi:10.3390/rs70505160 In this study, an in situ application for identifying neodymium (Nd) enriched surface materials that uses multitemporal hyperspectral images is presented (HySpex sensor). Because of the narrow shape and shallow absorption depth of the neodymium absorption feature, a method was developed for enhancing and extracting the necessary information for neodymium from image spectra, even under illumination conditions that are not optimal. For this purpose, the two following approaches were developed: (1) reducing noise and analyzing changing illumination conditions by averaging multitemporal image scenes and (2) enhancing the depth of the desired absorption band by deconvolving every image spectrum with a Gaussian curve while the rest of the spectrum remains unchanged (Richardson-Lucy deconvolution). To evaluate these findings, nine field samples from the Fen complex in Norway were analyzed using handheld X-ray fluorescence devices and by conducting detailed laboratory-based geochemical rare earth element determinations. The result is a qualitative outcrop map that highlights zones that are enriched in neodymium. To reduce the influences of non-optimal illumination, particularly at the studied site, a minimum of seven single acquisitions is required. Sharpening the neodymium absorption band allows for robust mapping, even at the outer zones of enrichment. From the geochemical investigations, we found that iron oxides decrease the applicability of the method. However, iron-related absorption bands can be used as secondary indicators for sulfidic ore zones that are mainly enriched with rare earth elements. In summary, we found that hyperspectral spectroscopy is a noninvasive, fast and cost-saving method for determining neodymium at outcrop surfaces.
2015
Hyperspectral and multispectral remote sensing for mapping grassland vegetation,

Ph.D Thesis for Thomas Möckel, DOI: 10.13140/RG.2.1.2745.4564

Hyperspectral and multispectral remote sensing for mapping grassland vegetation Thomas Möckel Ph.D Thesis for Thomas Möckel, DOI: 10.13140/RG.2.1.2745.4564 As a consequence of agricultural intensification, large areas of species-rich grasslands have been lost and farmland biodiversity has declined. Previous studies have shown that the continuity of grazing management can have a significant influence on the environmental conditions and the levels of plant species diversity in grassland habitats. The preservation of species-rich grasslands has become a high conservation priority within the European Union and the mapping of grazed grassland vegetation across wide areas has been identified as a central task for biodiversity conservation in agricultural landscapes. The fact that detailed field inventories of plant communities are time-consuming may limit the spatial extent of grassland habitat surveys. If remote sensing data are able to identify grassland sites characterised by different environmental conditions and plant species diversity, then field sampling efforts could be directed towards sites that are of potential conservation interest. In the thesis, I have examined the potential of hyperspectral and multispectral remote sensing imagery to map grassland vegetation at detailed scales in dry grazed grassland habitats. Fieldwork included the recording of vascular plant species and environmental variables in grasslands plots representing three age-classes within an arable-to-grassland succession in an agricultural landscape on the Baltic island of Öland (Sweden). Remotely sensed data were acquired with the help of two airborne HySpex hyperspectral spectrometers (415–2501 nm) and by the multispectral WorldView-2 satellite. The results of the thesis show that the soil nutrient and moisture status within grassland plots influenced the hyperspectral reflectance. Hyperspectral data had the ability to classify grassland plots into different age-classes. Hyperspectral reflectance measurements could be used to predict plant indicator values for nutrient and soil moisture in grassland plots. Prediction models developed from hyperspectral data were successfully used to assess levels of plant species diversity (species richness and Simpsons's diversity). In addition, between-plot dissimilarities in the satellite spectral reflectance were shown to be related to between-plot dissimilarities in the species composition in old grassland sites. The findings of the thesis demonstrate that remote sensing data are capable of capturing detailed-scale information that discriminates between grassland plant communities representing different environmental conditions and levels of plant species diversity. The results suggest that remote sensing data may have the ability for use as a decision-support tool to help conservation planners identify grassland habitats in agricultural landscapes that are of high conservation interest.
2015
The Potential of EnMAP and Sentinel-2 Data for Detecting Drought Stress Phenomena in Deciduous Forest Communities,

Remote Sensing 2015, 7, 14227-14258; doi:10.3390/rs71014227

The Potential of EnMAP and Sentinel-2 Data for Detecting Drought Stress Phenomena in Deciduous Forest Communities Sandra Dotzler, Joachim Hill, Henning Buddenbaum, Johannes Stoffels Remote Sensing 2015, 7, 14227-14258; doi:10.3390/rs71014227 Given the importance of forest ecosystems, the availability of reliable, spatially explicit information about the site-specific climate sensitivity of tree species is essential for implementing suitable adaptation strategies. In this study, airborne hyperspectral data were used to assess the response of deciduous species (dominated by European beech and Sessile and Pedunculate oak) to water stress during a summery dry spell. After masking canopy gaps, shaded crown areas and non-deciduous species, potentially indicative spectral indices, the Photochemical Reflectance Index (PRI), Moisture Stress Index (MSI), Normalized Difference Water Index (NDWI), and Chlorophyll Index (CI), were analyzed with respect to available maps of site-specific soil moisture regimes. PRI provided an important indication of site-specific photosynthetic stress on leaf level in relation to limitations in soil water availability. The CI, MSI and NDWI revealed statistically significant differences in total chlorophyll and water concentration at the canopy level. However, after reducing the canopy effects by normalizing these indices with respect to the structure-sensitive simple ratio (SR) vegetation index, it was not yet possible to identify site-specific concentration differences in leaf level at this early stage of the drought. The selected indicators were also tested with simulated EnMAP and Sentinel-2 data (derived from the original airborne data set). While PRI proved to be useful also in the spatial resolution of EnMAP (GSD = 30 m), this was not the case with Sentinel-2, owing to the lack of adequate spectral bands; the remaining indicators (MSI, CI, SR) were also successfully produced with Sentinel-2 data at superior spatial resolution (GSD = 10 m). The study confirms the importance of using earth observation systems for supplementing traditional ecological site classification maps, particularly during dry spells and heat waves when ecological gradients are increasingly reflected in the spectral response at the tree crown level. It also underlined the importance of using Sentinel-2 and EnMAP in synergy, as soon as both systems become available.
2015
Geological Application of HySpex Ground Hyperspectral Remote Sensing in Gold and Uranium Ore Deposits,

Asia-Pacific Energy Equipment Engineering Research Conference (AP3ER 2015)

Geological Application of HySpex Ground Hyperspectral Remote Sensing in Gold and Uranium Ore Deposits Yu Sun, Yingjun Zhao, Kai Qui, Jiangtao Nie, Haobo Li Asia-Pacific Energy Equipment Engineering Research Conference (AP3ER 2015) Hyperspectral remote sensing is a frontier field of remote sensing due to its advantage of object recognition based on spectral characteristics. This study carried out geological application of HySpex ground-based hyperspectral data at scales of both alteration belt in the Asiha gold district of Qinghai Province, and core in Xiangshan uranium deposit of Jiangxi Province. After data preprocessing, eight kinds of hydrothermal alteration minerals, such as hematite, sericite and illite, were extracted by the MTMF mapping method based on expert knowledge. Then, three alteration zones were divided in the gold deposit and six alteration zones were divided in the uranium core. The alteration minerals types, combination and distribution were further analyzed. It is concluded that alteration minerals closely related to the gold mineralization are limonite and sericite, and those closely associated with the uranium mineralization are hematite, illite and chlorite. Thus, HySpex data have a widespread prospect in basic geology survey and mineral exploration, for that their high spatial resolution can generate large-scale images, and that their high spectral resolution can identify alteration minerals.
2015
Detection and quantification of peanut traces in wheat flour by near infrared hyperspectral imaging spectroscopy using principal-component analysis,

JOURNAL OF NEAR INFRARED SPECTROSCOPY (01/2015).

Detection and quantification of peanut traces in wheat flour by near infrared hyperspectral imaging spectroscopy using principal-component analysis Puneet Mishra, Ana Herrero-Langreo, Pilar Barreiro, Jean-Michel Roger, Belen Diezma-Iglesias, Nathalie Gorretta-Monteiro, Lourdes Lleó JOURNAL OF NEAR INFRARED SPECTROSCOPY (01/2015). Use of a common environment for processing different powder foods in the industry has increased the risk of finding peanut traces in powder foods. The analytical methods commonly used for detection of peanut such as Enzyme-Linked Immunosorbent Assay (ELISA) and Real Time Polymerase Chain Reaction (RT-PCR) represent high specificity and sensitivity but are destructive, time consuming and require human involvement with high experimentation skills. The feasibility of NIR hyperspectral imaging (HSI) is studied for the detection of peanut traces down to 0.01% by weight. Principal Component Analysis (PCA) was carried out on a dataset of peanut and flour spectra. The obtained loadings were applied to the HSI images of adulterated wheat flour samples with peanut traces. As a result, HSI images were reduced to score images with enhanced contrast between peanut and flour particles. Finally, a threshold was fixed in score images to obtain a binary classification image and the percentage of peanut adulteration was compared to the percentage of pixels identified as peanut particles. This study allowed the detection of traces of peanut down to 0.01% and quantification of peanut adulteration from 10% to 0.1% with a coefficient of determination (r2) of 0.946. These results show the feasibility of using HIS systems for the detection of peanut traces in conjunction with chemical procedures, such as RT-PCR and ELISA to facilitate enhanced quality control surveillance on food product processing lines.
2014
Fusion trees for fast and accurate classification of hyperspectral data with ensembles of gamma-divergence-based RBF networks,

Neural Computing and Applications, 2014, 25, 1-10

Fusion trees for fast and accurate classification of hyperspectral data with ensembles of gamma-divergence-based RBF networks U. Knauer, Andreas Backhaus, Udo Seiffert Neural Computing and Applications, 2014, 25, 1-10
2014
State of the art of ground-based hyperspectral imaging in geo-science applications,

Proceedings of the first Vertical Geology Conference, 5 - 7 February 2014, University of Lausanne, Switzerland, 3-6.

State of the art of ground-based hyperspectral imaging in geo-science applications Tobias H. Kurz, Simon J. Buckley, John A. Howell Proceedings of the first Vertical Geology Conference, 5 - 7 February 2014, University of Lausanne, Switzerland, 3-6.
2014
Detection of raw materials in waste sites from iron and steel production using multi-scale spectral and lidar measurement: Case study from Thuringia, Germany.,

Proceedings of the first Vertical Geology Conference, 5 - 7 February 2014, University of Lausanne, Switzerland, 33-36.

Detection of raw materials in waste sites from iron and steel production using multi-scale spectral and lidar measurement: Case study from Thuringia, Germany. Michael Denk, Cornelia Gläßer, Tobias H. Kurz, Simon J. Buckley, D. MUDERSBACH, Peter Drissen Proceedings of the first Vertical Geology Conference, 5 - 7 February 2014, University of Lausanne, Switzerland, 33-36.
2014
Wavelet based feature extraction and visualization in hyperspectral tissue characterization,

Biomedical optics express 5 (12), 4260-4280

Wavelet based feature extraction and visualization in hyperspectral tissue characterization Martin Denstedt, Asgeir Bjorgan, Matija Milanic, Lise Randeberg Biomedical optics express 5 (12), 4260-4280
2014
Abbildende und nichtabbildende Geländespektrometrie zur Untersuchung von Stressphänomenen an Buchenpflanzen,

Photogrammetrie - Fernerkundung - Geoinformation, 2014 (1): 17-26. http://dx.doi.org/10.1127/1432-836412014/0207

Abbildende und nichtabbildende Geländespektrometrie zur Untersuchung von Stressphänomenen an Buchenpflanzen O. Stern, B. Paschmionka, Johannes Stoffels, Henning Buddenbaum, Joachim Hill Photogrammetrie - Fernerkundung - Geoinformation, 2014 (1): 17-26. http://dx.doi.org/10.1127/1432-836412014/0207
2014
On the quality evaluation of spectral image processing algorithms,

10th International Conference on Signal Image Technology & Internet Systems (SITIS)

On the quality evaluation of spectral image processing algorithms Hilda Deborah, N. Richard, Jon Yngve Hardeberg 10th International Conference on Signal Image Technology & Internet Systems (SITIS)
2014
Semi-automated registration of close range hyperspectral scans using oriented digital camera imagery and a 3D model.,

Photogrammetric Record, 29(145): 10-29. doi:10.1111/phor.12049.

Semi-automated registration of close range hyperspectral scans using oriented digital camera imagery and a 3D model. Aleksandra Sima, Simon J. Buckley, Tobias H. Kurz, Danilo Schneider Photogrammetric Record, 29(145): 10-29. doi:10.1111/phor.12049. Diverse applications can benefit from the integration of data acquired by a new generation of close-range imaging sensors with high-resolution three-dimensional (3D) geometric data. However, such integration requires increased automation and efficiency of image-data registration to guarantee adoption by users beyond the geomatics community. This paper presents a semi-automated method for registering terrestrial panoramic hyperspectral imagery with lidar models and conventional digital photography. The method relies on finding corresponding points between images acquired in significantly different parts of the electromagnetic spectrum, from different viewpoints, and with different spatial resolution and geometric projections. Optimisation of the scale invariant feature transform (SIFT) operator was required to ensure a sufficient number of homologous points, as well as a routine for eliminating false matches. A band selection routine maximises the number of points found while minimising the input data for SIFT. Three-dimensional object coordinates were derived in the lidar model and used as control points in a bundle block adjustment to determine the hyperspectral exterior orientation and intrinsic camera parameters. The method developed was applied to two datasets with different characteristics, and the results indicate that the proposed method is a time-saving alternative to manual approaches.
2014
APPLICATION OF REFLECTIVE HYPERSPECTRAL IMAGERY FOR HYDROCARBON SPILLS DETECTION,

IGARSS, Quebec, Canada, July 2014

APPLICATION OF REFLECTIVE HYPERSPECTRAL IMAGERY FOR HYDROCARBON SPILLS DETECTION Jean-Pierre Ardouin, François Lemieux, Vincent Roy IGARSS, Quebec, Canada, July 2014 Defence R&D Canada has been studying the military applications of hyperspectral imagery for many years [1]. More recently we were brought to investigate whether hyperspectral remote sensing could be used for the detection of liquid hydrocarbon spills in two applications of interest to the Canadian department of national defense (DND). The first application is related to search and rescue. DND is the lead ministry responsible for providing and coordinating search and rescue operations for incidents involving aircraft that occur both on land as well as in all of Canada's ocean and inland waters. Such incidents may involve the spills of aircraft fuel which will be one feature (among many) present at a crash site and that can potentially be used to search for the location of the crash. The other application is related to DND DEW Line Clean-Up project (DLCU) [2]. The old radar sites of the Defence Early Warning (DEW) line were constructed in the Canadian arctic in the 1950s and were no longer needed in the 1990s and thus scheduled for demolition. The DLCU project was mandated to assess and remove the contaminants and hazardous material at those sites. Although the contamination is not severe, DND is responsible to monitor the remaining landfills. We were asked to evaluate whether hyperspectral remote sensing could be used to monitor the DEW line landfills over all the sites located across the Canadian arctic and thus potentially lower the cost of doing this monitoring. Diesel fuel is one of the potential contaminants that we were asked to investigate. To study these potential applications, we conducted some experiments where we measured different type of liquid hydrocarbon spills using ground-based spectrometers and airborne hysperspectral sensors operating in the solar reflective region of the spectrum from approximately 400 to 2500 nm. In this paper we describe our experiments and present some preliminary results.
2014
A new dataset for analysis of hyperspectral target detection performance,

Hyperspectral Imaging and Applications Conference, October 2014, Coventry UK

A new dataset for analysis of hyperspectral target detection performance J. Piper, D. Clarke, William Oxford Hyperspectral Imaging and Applications Conference, October 2014, Coventry UK One of the key applications of hyperspectral imaging in the defence and security context is the detection of small targets in imagery collected by airborne platforms, based on the targets' spectral reflectance signatures. The Defence Science and Technology Laboratory (Dstl) has collected a dataset which is designed to support assessment of algorithms that perform this task, and which can be made available to the hyperspectral research community. This dataset includes a large number of targets with significant variation in the expected ease of detection, in order to provide a useful test for systems of various levels of performance. The differences in ease of detection are driven by the range of: pixel fill-factors; target materials, some of which are more spectrally distinctive than others; background materials; altitudes; and illumination conditions, with collections at different times of day and some targets being in shadow from clouds or objects on the ground. Imagery from various areas with no targets deployed is also included in the dataset, in order to provide information on the statistics of clutter in real environments (rural and urban). It is intended that this dataset will complement existing data (e.g. [1]) by providing information based on different sensors, target materials, context and environmental conditions.
2014
Application of Improved Direct Calibration for processing hyperspectral images to detect peanut traces in wheat flour,

Food Analysis Congress - 2014, Barcelona

Application of Improved Direct Calibration for processing hyperspectral images to detect peanut traces in wheat flour Puneet Mishra Food Analysis Congress - 2014, Barcelona
2014
Super Resolution Laser Radar with Blinking Atmospheric Particles - Application to Interacting Flying Insects,

Progress In Electromagnetics Research, Vol. 147, 141-151, 2014

Super Resolution Laser Radar with Blinking Atmospheric Particles - Application to Interacting Flying Insects Mikkel Brydegaard, Alem Gebru, Sune Svanberg Progress In Electromagnetics Research, Vol. 147, 141-151, 2014 Assessment of biodiversity of pollinators on the landscape scale or estimation of fluxes of disease-transmitting biting midges constitutes a major technical challenge today. We have developed a laser-radar system for field entomology based on the so called Scheimpflug principle and a continuouswave laser. The sample-rate of this method is unconstrained by the round-trip time of the light, and the method allows assessment of the fast oscillatory insect wing-beats and harmonics over kilometers range, e.g., for species identification and relating abundances to the topography. Whereas range resolution in conventional lidars is limited by the pulse duration, systems of the Scheimpflug type are limited by the diffraction of the telescopes. However, in the case of sparse occurrence of the atmospheric insects, where the optical cross-section oscillates, estimation of the range and spacing between individuals with a precision beyond the diffraction limit is now demonstrated. This enables studies of insect interaction processes in-situ.
2014
IMPROVING HYSPEX SENSOR CO-REGISTRATION ACCURACY USING BRISK AND SENSOR-MODEL BASED RANSAC,

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-1, 2014, ISPRS Technical Commission I Symposium, 17- 20 November 2014, Denver, Colorado, USA

IMPROVING HYSPEX SENSOR CO-REGISTRATION ACCURACY USING BRISK AND SENSOR-MODEL BASED RANSAC Peter Schwind, Mathias Schneider, Rupert Muller The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-1, 2014, ISPRS Technical Commission I Symposium, 17- 20 November 2014, Denver, Colorado, USA In this paper a method to improve the co-registration accuracy of two separate HySpex SWIR and VNIR cameras is proposed. The first step of the presented approach deals with the detection of point features from both scenes using the BRISK feature detector. After matching these features, the match coordinates in the VNIR scene are orthorectified and the resulting ground control points in the SWIR scene are filtered using a sensor-model based RANSAC. This implementation of RANSAC estimates the boresight angles of a scene by iteratively fitting the sensor-model to a subset of the matches. The boresight angles which can be applied to most of the remaining matches are then used to orthorectify the scene. Compared to previously used methods, the main advantages of this approach are the high robustness against outliers and the reduced runtime. The proposed methodology was evaluated using a test data set and it is shown in this work that the use of BRISK for feature detection followed by sensor-model based RANSAC significantly improves the co-registration accuracy of the imagery produced by the two HySpex sensors.
2014
Modified multiple endmember spectral mixture analysis for mapping impervious surfaces in urban environments,

Journal of Applied Remote Sensing 085096-1 Vol. 8, 2014

Modified multiple endmember spectral mixture analysis for mapping impervious surfaces in urban environments Kun Tan, Xiao Jin, Qian Du, Peijun Du Journal of Applied Remote Sensing 085096-1 Vol. 8, 2014 A modified multiple endmember spectral mixture analysis (MMESMA) approach is proposed for high-spatial-resolution hyperspectral imagery in the application of impervious surface mapping. Different from the original MESMA that usually selects one endmember spectral signature for each land-cover class, the proposed MMESMA allows the selection of multiple endmember signatures for each land-cover class. It is expected that the MMESMA can better accommodate within-class variations and yield better mapping results. Various unmixing models are compared, such as the linear mixing model, linear spectral mixture analysis using the original linear mixture model, original MESMA, and support vector machine using a nonlinear mixture model. Airborne 1-m resolution HySpex and ROSIS data are used in the experiments. For HySpex data, validation based on 25-cm synchronism aerial photography shows that MMESMA performs the best, with the root-mean-squared error (RMSE) of the estimated abundance fractions being 13.20% and the correlation coefficient (R2) being 0.9656. For ROSIS data, validation based on simulation shows that MMESMA performs the best, with the RMSE of the estimated abundance fraction being 4.51% and R2 being 0.9878. These demonstrate that the proposed MMESMA can generate more reliable abundance fractions for high-spatial-resolution hyperspectral imagery, which tends to include strong within-class spectral variations.
2014
EVALUATION BREFCOR BRDF EFFECTS CORRECTION FOR HYSPEX, CASI, AND APEX IMAGING SPECTROSCOPY DATA,

IEEE WHISPERS, Lausanne, 2014, pp. 4.

EVALUATION BREFCOR BRDF EFFECTS CORRECTION FOR HYSPEX, CASI, AND APEX IMAGING SPECTROSCOPY DATA Daniel Schläpfer, Rudolf Richter IEEE WHISPERS, Lausanne, 2014, pp. 4. The correction of BRDF effects for airborne wide FOV imaging spectroscopy data is of interest for a consistent data processing and products generation. Recently, a new BRDF effects correction method (BREFCOR) has been implemented as additional processing step after the well-known atmospheric compensation workflow. This paper shows validation results of the method for sample data sets of HYSPEX, CASI, and APEX data. It can be shown that the method is able to deal with a broad variety of sensors and surface characteristics. The spectral albedo data products are substantially increased in terms of consistency for all data sets. Future potential improvements and additions for a better operational usability and for the processing of complete spectra are finally summarized.
2014
HySpex ODIN-1024: a new high-resolution airborne HSI system,

Proc. SPIE 9070, Infrared Technology and Applications XL, 90700L (June 24, 2014); doi:10.1117/12.2063502

HySpex ODIN-1024: a new high-resolution airborne HSI system Søren Blaaberg, Trond Løke, Ivar Baarstad, Andrei Fridman, Pesal Koirala Proc. SPIE 9070, Infrared Technology and Applications XL, 90700L (June 24, 2014); doi:10.1117/12.2063502 HySpex ODIN-1024 is a next generation state-of the-art airborne hyperspectral imaging system developed by Norsk Elektro Optikk AS. Near perfect coregistration between VNIR and SWIR is achieved by employing a novel common fore-optics design and a thermally stabilized housing. Its unique design and the use of state-of-the-art MCT and sCMOS sensors provide the combination of high sensitivity and low noise, low spatial and spectral misregistration (smile and keystone) and a very high resolution (1024 pixels in the merged data products). In addition to its supreme data quality, HySpex ODIN-1024 includes real-time data processing functionalities such as real-time georeferencing of acquired images. It also features a built-in onboard calibration system to monitor the stability of the instrument. The paper presents data and results from laboratory tests and characterizations, as well as results from airborne measurements.
2014
Nonlinear Unmixing of Hyperspectral Images,

IEEE SIGNAL PROCESSING MAGAZINE [82] JANUARY 2014, 10.1109/MSP.2013.2279274

Nonlinear Unmixing of Hyperspectral Images Nicolas Dobigeon, Jean-Yves Tourneret, Cédric Richard, José Carlos M. Bermudez, Steve McLaughlin, Alfred O. Hero IEEE SIGNAL PROCESSING MAGAZINE [82] JANUARY 2014, 10.1109/MSP.2013.2279274
2014
Identification of inflammation sites in arthritic joints using hyperspectral imaging,

Proc. SPIE 8947, Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues XII, 89470H (March 4, 2014); doi:10.1117/12.2040499

Identification of inflammation sites in arthritic joints using hyperspectral imaging Lukasz A. Paluchowski, Matija Milanic, Asgeir Bjorgan, Berit Grandaunet, Alvilde Dhainaut, Mari Hoff, Lise Randeberg Proc. SPIE 8947, Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues XII, 89470H (March 4, 2014); doi:10.1117/12.2040499 Inflammatory arthritic diseases have prevalence between 2 and 3% and may lead to joint destruction and deformation resulting in a loss of function. Patient’s quality of life is often severely affected as the disease attacks hands and finger joints. Pathology involved in arthritis includes angiogenesis, hyper-vascularization, hyper-metabolism and relative hypoxia. We have employed hyperspectral imaging to study the hemodynamics of affected- and non-affected joints and tissue. Two hyperspectral, push-broom cameras were used (VNIR-1600, SWIR-320i, Norsk Elektro Optikk AS, Norway). Optical spectra (400nm – 1700nm) of high spectral resolution were collected from 15 patients with visible symptoms of arthritic rheumatic diseases in at least one joint. The control group consisted of 10 healthy individuals. Concentrations of dominant chromophores were calculated based on analytical calculations of light transport in tissue. Image processing was used to analyze hyperspectral data and retrieve information, e.g. blood concentration and tissue oxygenation maps. The obtained results indicate that hyperspectral imaging can be used to quantify changes within affected joints and surrounding tissue. Further improvement of this method will have positive impact on diagnosis of arthritic joints at an early stage. Moreover it will enable development of fast, noninvasive and noncontact diagnostic tool of arthritic joints.
2014
Hyperspectral characterization of an in vitro wound model,

JProc. SPIE 8926, Photonic Therapeutics and Diagnostics X, 892607 (March 4, 2014); doi:10.1117/12.2039976

Hyperspectral characterization of an in vitro wound model Lise Randeberg, Janne-Lise Hegstad, Lukasz A. Paluchowski, Matija Milanic, Brita S. Pukstad JProc. SPIE 8926, Photonic Therapeutics and Diagnostics X, 892607 (March 4, 2014); doi:10.1117/12.2039976 Wound healing is a complex process not fully understood. There is a need of better methods to evaluate the different stages of healing, and optical characterization is a promising tool in this respect. In this study hyperspectral imaging was employed to characterize an in vitro wound model. The wound model was established by first cutting circular patches of human abdominal skin using an 8mm punch biopsy tool, and then creating dermal wounds in the center of the skin patches using a 5mm tool. The wounds were incubated in medium with 10% serum and antibiotics. Hyperspectral images were collected every three days using a push broom hyper spectral camera (Hyspex VNIR1600). The camera had a spectral resolution of 3.7 nm and was fitted with a close up lens giving a FOV of 2.5 cm and a spatial resolution of 29 micrometer. Samples for histology were collected throughout the measurement period, which was 21 days in total. Data were processed in ENVI and Matlab. A successful classification based on hyperspectral imaging of the implemented model is presented. It was not possible to see the healing zone in the in vitro model with the naked eye without dying. The hyperspectral results showed that newly formed epithelium could be imaged without any additional contrast agents or dyes. It was also possible to detect non-viable tissue. In vitro wound models and hyperspectral imaging can thus be employed to gain further insight in the complicated process of healing in different kinds of wounds. © (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
2014
Fine spatial resolution mapping of soil organic matter quality in a Histosol profile.,

European Journal of Soil Science Volume: 65 Issue: 6 Pages: 827-839

Fine spatial resolution mapping of soil organic matter quality in a Histosol profile. Markus Steffens, Michael Kohlpaintner, Henning Buddenbaum European Journal of Soil Science Volume: 65 Issue: 6 Pages: 827-839 Soil science lacks a fine spatial resolution imaging technique that is able to measure the quantity and quality of organic matter (OM) for complete soil profiles. We tested whether laboratory Vis-NIR imaging spectroscopy, together with an unsupervised k-means classification, can be used to distinguish between different OM fractions in a Histosol profile. A rectangular soil column (22-cm long) of a folic Histosol (Tangelhumus) was collected from an alpine Norway spruce forest in south-eastern Germany with a stainless steel box (100 × 100 × 300 mm). A hyperspectral camera (400–1000 nm with 160 bands) with a pixel sampling of 63 × 63 µm was used to acquire the data. We took images of three vertical cuts through the soil profile, each separated laterally by 25 mm. Reference samples were taken at representative locations and analysed for soil organic matter (SOM) quantity and quality with a CN elemental analyser and solid-state 13C nuclear magnetic resonance (NMR) spectroscopy. Principal component analysis and unsupervised k-means classifications were used to discriminate between different qualities of OM. We identified three OM fractions based on their reflectance characteristics: living and dead roots with a small degree of decomposition, decomposed particulate OM and decomposed amorphous OM. These fractions were consistent with the morpho-functional classes of two soil classification systems and can be used for the improved identification of diagnostic horizons. The spectra of the fractions contained additional information on, for example, lignin content and the degree of decomposition. Vis-NIR imaging spectroscopy is a powerful technique for mapping SOM quality in visually homogeneous organic surface layers.
2014
Estimation of skin optical parameters for real-time hyperspectral imaging applications.,

Journal of Biomedical Optics 19(6), 066003 (June 2014)

Estimation of skin optical parameters for real-time hyperspectral imaging applications. Asgeir Bjorgan, Matija Milanic, Lise Randeberg Journal of Biomedical Optics 19(6), 066003 (June 2014) Hyperspectral imaging combines high spectral and spatial resolution in one modality. This imaging technique is a promising tool for objective medical diagnostics. However, to be attractive in a clinical setting, the technique needs to be fast and accurate. Hyperspectral imaging can be used to analyze tissue properties using spectroscopic methods, and is thus useful as a general purpose diagnostic tool. We combine an analytic diffusion model for photon transport with real-time analysis of the hyperspectral images. This is achieved by parallelizing the inverse photon transport model on a graphics processing unit to yield optical parameters from diffuse reflectance spectra. The validity of this approach was verified by Monte Carlo simulations. Hyperspectral images of human skin in the wavelength range 400–1000 nm, with a spectral resolution of 3.6 nm and 1600 pixels across the field of view (Hyspex VNIR-1600), were used to develop the presented approach. The implemented algorithm was found to output optical properties at a speed of 3.5 ms per line of image data. The presented method is thus capable of meeting the defined real-time requirement, which was 30 ms per line of data.The algorithm is a proof of principle, which will be further developed
2014
Pigment Mapping of the Scream (1893) Based on Hyperspectral Imaging,

Image and Signal Processing, Lecture Notes in Computer Science Volume 8509, 2014, pp 247-256

Pigment Mapping of the Scream (1893) Based on Hyperspectral Imaging Hilda Deborah, Sony George, Jon Yngve Hardeberg Image and Signal Processing, Lecture Notes in Computer Science Volume 8509, 2014, pp 247-256 Hyperspectral imaging is a promising non-invasive method for applications in conservation of painting. With its ability to capture both spatial and spectral information which relates to physical characteristics of materials, the identification of pigments and its spatial distribution across the painting is now possible. In this work, The Scream (1893) by Edvard Munch is acquired using a hyperspectral scanner and the pigment mapping of its constituent pigments are carried out. Two spectral image classification methods, i.e. Spectral Angle Mapper (SAM) and Spectral Correlation Mapper (SCM), and a fully constrained spectral unmixing algorithm combined with linear mixing model are employed for the pigment mapping of the painting.
2014
A case study at Starnberger See for hyperspectral bathymetry mapping using inverse modeling.,

Presented at WHISPERS, June 25-27, 2014, Lausanne, Switzerland

A case study at Starnberger See for hyperspectral bathymetry mapping using inverse modeling. Peter Gege Presented at WHISPERS, June 25-27, 2014, Lausanne, Switzerland In coastal regions, hyperspectral remote sensing is becoming an established method to map water depth. For inland waters however, only few studies based on empirical methods have been published so far. This paper presents a study for the German lake Starnberger See using a physically based approach. Hyperspectral data were acquired from airplane using a HySpex VNIR-1600 sensor. They were processed by inverse modeling using a radiative-transfer based analytical model. In situ measurements were taken to decide which model parameters to fit and which to keep constant during data analysis, and they were used to initialize the parameters. Bottom reflectance was determined from the image itself. An echo sounding survey was undertaken for validation. For the studied area, bathymetry could be mapped up to a depth of 8 m with a rms error of 37 cm. Accuracies of 10-25 cm from 0-4 m and 35-65 cm from 4-8 m seem possible if the remaining systematic errors can be further reduced, e.g. by accounting for changes of bottom reflectance.
2014
Classification of Grassland Successional Stages Using Airborne Hyperspectral Imagery.,

Remote Sensing. 2014; 6(8):7732-7761.

Classification of Grassland Successional Stages Using Airborne Hyperspectral Imagery. Thomas Möckel, Jonas Dalmayne, Honor C. Prentice, Lars Eklundh, Oliver Purschke, Sebastian Schmidtlein, Karin Hall Remote Sensing. 2014; 6(8):7732-7761. Plant communities differ in their species composition, and, thus, also in their functional trait composition, at different stages in the succession from arable fields to grazed grassland. We examine whether aerial hyperspectral (414–2501 nm) remote sensing can be used to discriminate between grazed vegetation belonging to different grassland successional stages. Vascular plant species were recorded in 104.1 m2 plots on the island of Öland (Sweden) and the functional properties of the plant species recorded in the plots were characterized in terms of the ground-cover of grasses, specific leaf area and Ellenberg indicator values. Plots were assigned to three different grassland age-classes, representing 5–15, 16–50 and >50 years of grazing management. Partial least squares discriminant analysis models were used to compare classifications based on aerial hyperspectral data with the age-class classification. The remote sensing data successfully classified the plots into age-classes: the overall classification accuracy was higher for a model based on a pre-selected set of wavebands (85%, Kappa statistic value = 0.77) than one using the full set of wavebands (77%, Kappa statistic value = 0.65). Our results show that nutrient availability and grass cover differences between grassland age-classes are detectable by spectral imaging. These techniques may potentially be used for mapping the spatial distribution of grassland habitats at different successional stages.
2014
Resampling in hyperspectral cameras as an alternative to correcting keystone in hardware, with focus on benefits for the optical design and data quality,

Optical Engineering 53(5), 053107 (May 2014)

Resampling in hyperspectral cameras as an alternative to correcting keystone in hardware, with focus on benefits for the optical design and data quality Andrei Fridman, Gudrun Høye, Trond Løke Optical Engineering 53(5), 053107 (May 2014) Current high-resolution hyperspectral cameras attempt to correct misregistration errors in hardware. Usually, it is required that aberrations in the optical system must be controlled with precision 0.1 pixel or smaller. This severely limits other specifications of the hyperspectral camera, such as spatial resolution and light gathering capacity, and often requires very tight tolerances. If resampling is used to correct keystone in software instead of in hardware, then these stringent requirements could be lifted. Preliminary designs show that a resampling camera should be able to resolve at least 3000-5000 pixels, while at the same time collecting up to four times more light than the majority of current high spatial resolution cameras that correct keystone in hardware (HW corrected cameras). A Virtual Camera software, specifically developed for this purpose, was used to compare the performance of resampling cameras and HW corrected cameras. For the cameras where a large keystone is corrected by resampling, different resampling methods are investigated. Different criteria are suggested for quantifying performance, and the tested cameras are compared according to these criteria. The simulations showed that the performance of a resampling camera is comparable to that of a HW corrected camera with 0.1 pixel residual keystone, and that the use of a more advanced resampling method than the commonly used linear interpolation - such as for instance high-resolution cubic splines - is highly beneficial for the data quality of the resampled image. Our findings suggest that if high-resolution sensors are available, it would be better to use resampling instead of trying to correct keystone in hardware.
2013
Quantitative Measurements of model interpretability for the analysis of spectral data,

Computational Intelligence and Data Mining (CIDM), 2013 IEEE Symposium on, 2013, 18-25

Quantitative Measurements of model interpretability for the analysis of spectral data Andreas Backhaus, Udo Seiffert Computational Intelligence and Data Mining (CIDM), 2013 IEEE Symposium on, 2013, 18-25
2013
Close-range hyperspectral imaging for geological field studies: workflow and methods,

International Journal of Remote Sensing, 34(5): 1798-1822. doi:10.1080/01431161.2012.727039.

Close-range hyperspectral imaging for geological field studies: workflow and methods Tobias H. Kurz, Simon J. Buckley, John A. Howell International Journal of Remote Sensing, 34(5): 1798-1822. doi:10.1080/01431161.2012.727039.
2013
Optimizing SIFT for Matching of Short Wave Infrared and Visible Wavelength Images,

Remote Sensing, 5(5): 2037-2056. doi:10.3390/rs5052037.

Optimizing SIFT for Matching of Short Wave Infrared and Visible Wavelength Images Aleksandra Sima, Simon J. Buckley Remote Sensing, 5(5): 2037-2056. doi:10.3390/rs5052037.
2013
Terrestrial lidar and hyperspectral data fusion products for geological outcrop analysis,

Computers & Geosciences, 54: 249-258. doi:10.1016/j.cageo.2013.01.018.

Terrestrial lidar and hyperspectral data fusion products for geological outcrop analysis Simon J. Buckley, Tobias H. Kurz, John A. Howell, Danilo Schneider Computers & Geosciences, 54: 249-258. doi:10.1016/j.cageo.2013.01.018.
2013
Hyperspectral imaging as a diagnostic tool for chronic skin ulcers,

SPIE BiOS, 85650N-85650N-14

Hyperspectral imaging as a diagnostic tool for chronic skin ulcers Martin Denstedt, Brita S. Pukstad, Lukasz A. Paluchowski, Julio Ernesto Hernández Palacios, Lise Randeberg SPIE BiOS, 85650N-85650N-14
2013
A combined 3D and hyperspectral method for surface imaging of wounds,

SPIE BiOS, 85780T-85780T-10

A combined 3D and hyperspectral method for surface imaging of wounds Lukasz A. Paluchowski, Martin Denstedt, Thomas Røren, Brita S. Pukstad, Lise Randeberg SPIE BiOS, 85780T-85780T-10
2013
Combined hyperspectral and 3D characterization of non-healing skin ulcers,

Colour and Visual Computing Symposium (CVCS), 2013, 1-6

Combined hyperspectral and 3D characterization of non-healing skin ulcers Lise Randeberg, Martin Denstedt, Lukasz A. Paluchowski, Matija Milanic, Brita S. Pukstad Colour and Visual Computing Symposium (CVCS), 2013, 1-6
2013
Laboratory imaging spectroscopy of a stagnic Luvisol profile - high resolution soil characterisation, classification and mapping of elemental concentrations,

Geoderma, 195-196: 122-132. http://dx.doi.org/10.1016/j.geoderma.2012.11.011

Laboratory imaging spectroscopy of a stagnic Luvisol profile - high resolution soil characterisation, classification and mapping of elemental concentrations Markus Steffens, Henning Buddenbaum Geoderma, 195-196: 122-132. http://dx.doi.org/10.1016/j.geoderma.2012.11.011
2013
A collection of hyperspectral images for imaging systems research,

Proc. SPIE 8660, 86600C

A collection of hyperspectral images for imaging systems research Torbjørn Skauli, J. Farrell Proc. SPIE 8660, 86600C
2013
INVESTIGATION OF A PAINTING DATING THE FRENCH REVOLUTION USING VISIBLE AND NEAR INFRARED HYPERSPECTRAL IMAGERY,

IEEE Transactions on Geoscience and Remote Sensing, Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS, 25-28 June, Gainsville, Florida, 2013

INVESTIGATION OF A PAINTING DATING THE FRENCH REVOLUTION USING VISIBLE AND NEAR INFRARED HYPERSPECTRAL IMAGERY S. Le Mouélic, François Chauvet, Manuel Giraud, Erwan Le Menn, Caroline Leynia, Olivier Barbet IEEE Transactions on Geoscience and Remote Sensing, Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS, 25-28 June, Gainsville, Florida, 2013 We have investigated the potential of visible and infrared hyperspectral imagery to characterize a painting dating from the French revolution. Images at increasingly long wavelengths, probing different depths into the painting, revealed the chronology of the drawings used by the artist. It shows that the two main characters of the drawing have been painted first, followed by the surrounding buildings. The classification of the hyperspectral data set also allowed the automated detection of restored areas, thanks to a different response of the surface varnish. The analysis provided information about the painter technique and allowed the identification and the mapping of the distribution of the main pigments.
2013
Mapping Minerals on a Painting Dating the French Revolution Using Hyperspectral Imagery,

8th EARSeL SIG Imaging Spectroscopy Workshop, Nantes, France, 8 -10 April 2013

Mapping Minerals on a Painting Dating the French Revolution Using Hyperspectral Imagery Stéphane Le Mouélic, François Chauvet, Manuel Giraud, Erwan Le Menn, Caroline Leynia, Olivier Barbet 8th EARSeL SIG Imaging Spectroscopy Workshop, Nantes, France, 8 -10 April 2013 Visible and infrared imaging spectroscopy is a very efficient non destructive remote sensing tool to characterize the composition and physical state of a surface. In support for our applications in the domain of planetary exploration and Earth remote sensing, we have set up a laboratory facility to characterize hyperspectral signatures of well controlled mineral, rocks, or man-made artifacts. This experimental facility is built upon three HySpex cameras from the NEO company, covering the 0.4-1.0 μm, 0.9-1.7μm and 1.3-2.5 μm wavelength ranges with a working distance of either 0.3 m or 1 m. We have investigated the potential of visible and infrared hyperspectral imagery to characterize a painting dating from the French revolution : the “Club Breton” painting, belonging to the museum of Brittany in Rennes (France). Hyperspectral images of the painting have been acquired with the three cameras, using the painting mounted on a translation stage. Data have been calibrated in reflectance using a Spectralon as a reference. A series of Kremer pure pigments was also imaged with the cameras in order to provide a reference historical database. The classification of the hyperspectral data set allowed the automated detection of restored areas, thanks to a different response of the surface varnish. The analysis provided information about the painter technic. In particular, images at increasingly long wavelengths, probing different depths into the painting, revealed the chronology of the drawings used by the artist. It shows that the two main characters of the drawing have been painted first, followed by the surrounding buildings. The classification using the Spectral Angle Mapper algorithm allowed the identification and the mapping of the distribution of the main pigments.
2013
Estimation of Plastic Debris Loads in Aquatic Ecosystems from Water Samples Using Hyperspectral Imaging - a Case Study for Teltow Channel, Berlin,

The International Conference on Prevention and Management of Marine Litter in European Seas, Berlin, April, 2013.

Estimation of Plastic Debris Loads in Aquatic Ecosystems from Water Samples Using Hyperspectral Imaging - a Case Study for Teltow Channel, Berlin Thomas Lanners, Mathias Bochow, Sascha Oswald The International Conference on Prevention and Management of Marine Litter in European Seas, Berlin, April, 2013. Plastic debris, as a common persistent pollutant, is accumulating in marine and coastal habitats worldwide, yet the quantification of sources and pathways for land-based plastic pollution remains uncertain. Densely populated urban areas have been shown to contribute significantly to land-based plastic pollution by draining plastic-polluted waters through river systems to the oceans (Moore et al., 2011). (Un-) Conscious littering by consumers, poor handling during polymer processing and non-existing wastewater treatment for small plastic particles from household wastewaters are only some examples why urban areas are predestinated for having a huge impact on adjacent aquatic ecosystems in regard to plastic pollution. Up to now several studies have been carried out to show plastic debris accumulations near estuarine areas in the North Sea (e.g. Liebezeit & Dubaish, 2012). This study aims to trace back the pollution pathway to its source and uses the Teltow Channel as an ideally suited small-scale research area.
2013
CORRECTION OF SHADOWING IN IMAGING SPECTROSCOPY DATA BY QUANTIFICATION OF THE PROPORTION OF DIFFUSE ILLUMINATION,

8th SIG-IS EARSeL Imaging Spectroscopy Workshop, Nantes, 2013, pp. 10.

CORRECTION OF SHADOWING IN IMAGING SPECTROSCOPY DATA BY QUANTIFICATION OF THE PROPORTION OF DIFFUSE ILLUMINATION Daniel Schläpfer, Rudolf Richter, Alexander Damm 8th SIG-IS EARSeL Imaging Spectroscopy Workshop, Nantes, 2013, pp. 10. High spatial resolution imaging spectroscopy data is affected by various shadowing influences: be it the shadows of buildings, within forests, at forest borders, by single trees, by terrain, or by clouds. The radiometric performance of modern imaging spectroscopy systems provides a dynamic range which is large enough to retrieve useful spectral surface information even within full cast shadows. Thus, atmospheric correction routines should provide a capability to account for all above-mentioned types of cast shadows. The use of accurate surface models for cast shadow ray tracing does not lead to useful results in many cases as the surface representation with respect to the radiometry is never accurate enough. Therefore, an image-based method applicable to a broad variety of image data is searched. A method for cast shadow detection and correction has been implemented and included in the workflow of the ATCOR atmospheric compensation package. The shadows are retrieved from calibrated at-sensor radiance imagery relying on the fact that all areas in shade are illuminated by a large proportion of diffuse irradiance. The diffuse irradiance is caused by scattering in the atmosphere and thus exhibits very specific spectral characteristics compared to the direct irradiance. Specifically, the relative signal in the blue is significantly higher in areas affected by cast shadow than in directly illuminated regions. Specific indices have been defined to quantify the shadow fraction on a per-pixel basis by exploiting the spectral properties of illumination. This strategy results in a continuous quantification of the shadow field. The output is used directly in the atmospheric/topographic correction on the basis of the ATCOR model in a physical way. Tests of the procedure on various imaging spectroscopy data samples show significant improvements of surface reflectance products in forests and in urban areas. Validation results demonstrate the performance and indicate limitations of the proposed methods. Implications for the retrieval of remote sensing products are discussed, with a particular focus on the vegetation indices normalized difference vegetation index (NDVI) and photochemical reflectance index (PRI).
2013
Assessment of Cartographic potential of airborne hyperspectral data for large scale mapping,

Recent Advances in Image, Audio and Signal Processing, ISBN: 978-960-474-350-6

Assessment of Cartographic potential of airborne hyperspectral data for large scale mapping Lamyaa Gamal El-Deen Taha, Attia Abd Al Fattah Shahin Recent Advances in Image, Audio and Signal Processing, ISBN: 978-960-474-350-6 Hyperspectral imaging is used for a broad range of applications in remote sensing. To date, a majority of research has focused on natural targets such as vegetation and minerals. Far less research has focused on urban areas using hyperspectral data. This research is concerned with the investigation of large scale mapping from airborne hyperspectral data in order to know to what scale of airborne hyperspectral data is suitable for map production. Geometric correction using direct georefrencing and atmospheric correction have been performed. After that feature selection has been performed. Quality of rectification has been assessed using DGPS check points. A program has been developed using paython language for assessment of geopositioning accuracy of airborne hyperspectral data. It was found that the total RMS of airborne hyperspectral data was 0.4 m. The RMS was within the required standard map accuracy for a map 1:1000 according to the map accuracy standards of NMAS. Planimetric vector map has been produced using on screen digitizing. Automatic map production has been performed using ANN. It was found that the first method is faster than the second method and second method needs manual editing compared to the resulted vector map from on screen digitizing.
2013
Mixel camera - a new push-broom camera concept for high spatial resolution keystone-free hyperspectral imaging,

Optics Express, Vol. 21, Issue 9, pp. 11057-11077. http://dx.doi.org/10.1364/OE.21.011057

Mixel camera - a new push-broom camera concept for high spatial resolution keystone-free hyperspectral imaging Gudrun Høye, Andrei Fridman Optics Express, Vol. 21, Issue 9, pp. 11057-11077. http://dx.doi.org/10.1364/OE.21.011057 Current high-resolution push-broom hyperspectral cameras introduce keystone errors to the captured data. Efforts to correct these errors in hardware severely limit the optical design, in particular with respect to light throughput and spatial resolution, while at the same time the residual keystone often remains large. The mixel camera solves this problem by combining a hardware component--an array of light mixing chambers--with a mathematical method that restores the hyperspectral data to its keystone-free form, based on the data that was recorded onto the sensor with large keystone. A Virtual Camera software, that was developed specifically for this purpose, was used to compare the performance of the mixel camera to traditional cameras that correct keystone in hardware. The mixel camera can collect at least four times more light than most current high-resolution hyperspectral cameras, and simulations have shown that the mixel camera will be photon-noise limited--even in bright light--with a significantly improved signal-to-noise ratio compared to traditional cameras. A prototype has been built and is being tested.
2013
Opalisation of the Great Artesian Basin (central Australia): An Australian Story with a Martian Twist,

Australian Journal of Earth Sciences

Opalisation of the Great Artesian Basin (central Australia): An Australian Story with a Martian Twist Patrice Rey Australian Journal of Earth Sciences This paper exposes the unique set of attribute explaining why precious opal has formed in such abundance in central Australia, and almost nowhere else on Earth. The Early Cretaceous history of the Great Artesian Basin is that of a high-latitude flexural foreland basin associated to a Cordillera Orogen built along the Pacific margin of Gondwana. The basin, flooded by the Eromanga Sea, acted as a sink for volcaniclastic sediments eroded from the Cordillera’s volcanic arc. The Eromanga Sea was shallow, cold, poorly connected to the open ocean, muddy and stagnant, which explains the absence of significant carbonates. Iron-rich and organic matterrich sediments contributed to the development of an anoxic sub-seafloor in which anaerobic, pyrite-producing bacteria thrived. Rich in pyrite, ferrous iron, feldspar, volcanic fragments and volcanic ash, Lower Cretaceous lithologies have an exceptionally large acidification potential and pH neutralisation capacity. This makes Lower Cretaceous lithologies particularly reactive to oxidative weathering. From 97 to 60 Ma, Australia remained at high latitude and a protracted period of uplift, erosion, denudation and crustal cooling unfolded. It is possibly during this period that the bulk of precious opal was formed via acidic oxidative weathering. When uplift stopped at ca 60 Ma, the opalised redox front was preserved by the widespread deposition of a veneer of Cenozoic sediments. On Earth, regional acidic weathering is rare. Interestingly, acidic oxidative weathering has been documented at the surface of Mars, which shares an intriguing set of attributes with the Great Artesian Basin including: i) volcaniclastic lithologies; ii) absence of significant carbonate; iii) similar secondary assemblages including opaline silica; iv) similar acidic oxidative weathering driven by very similar surface drying out; and, not surprisingly, v) the same colour. This suggests that the Australian red centre could well be the best regional terrestrial analogue for the surface of the red planet.
2012
The benefits of terrestrial laser scanning and hyperspectral data fusion products.,

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 39(B7): 541-546. doi:10.5194/isprsarchives-XXXIX-B7-541-2012.

The benefits of terrestrial laser scanning and hyperspectral data fusion products. Simon J. Buckley, Tobias H. Kurz, Danilo Schneider International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 39(B7): 541-546. doi:10.5194/isprsarchives-XXXIX-B7-541-2012.
2012
Intercomparison of EMCCD-and sCMOS-based imaging spectrometers for biomedical applications in low-light conditions,

SPIE BiOS, 82150Q-82150Q-9

Intercomparison of EMCCD-and sCMOS-based imaging spectrometers for biomedical applications in low-light conditions Julio Ernesto Hernández Palacios, Lise Randeberg SPIE BiOS, 82150Q-82150Q-9
2012
Hyperspectral Imaging as a Tool for Fluorescence Imaging and Characterization of Skin Bruises,

Imaging Systems and Applications, ITu2C. 1

Hyperspectral Imaging as a Tool for Fluorescence Imaging and Characterization of Skin Bruises Lise Randeberg, Julio Ernesto Hernández Palacios Imaging Systems and Applications, ITu2C. 1
2012
Field Imaging Spectroscopy of Beech Seedlings under Dryness Stress,

Remote Sensing, 4: 3721-3740. http://dx.doi.org/10.3390/rs4123721

Field Imaging Spectroscopy of Beech Seedlings under Dryness Stress Henning Buddenbaum, O. Stern, M. Stellmes, Johannes Stoffels, P. Pueschel, Joachim Hill, W. Werner Remote Sensing, 4: 3721-3740. http://dx.doi.org/10.3390/rs4123721
2012
Microphytobenthos biomass mapping using the optical model of diatom biofilms: Application to hyperspectral images of Bourgneuf Bay,

Remote Sensing of Environment 127 (2012) 1—13

Microphytobenthos biomass mapping using the optical model of diatom biofilms: Application to hyperspectral images of Bourgneuf Bay Farzaneh Kazemipour, Patrick Launeau, Vona Meleder Remote Sensing of Environment 127 (2012) 1—13
2012
Improving anomaly detection with multinormal mixture models in shadow,

IEEE International Symposium on Geoscience and Remote Sensing 2012, 5478-5481

Improving anomaly detection with multinormal mixture models in shadow Trym V. Haavardsholm, Amela Kavara, Ingebjørg Kåsen, Torbjørn Skauli IEEE International Symposium on Geoscience and Remote Sensing 2012, 5478-5481
2012
Semi-automatic Integration of Panoramic Hyperspectral Imagery with Photorealistic Lidar Models,

Photogrammetrie - Fernerkundung - Geoinformation, Volume 2012, Number 4, August 2012 , pp. 443-454(12)

Semi-automatic Integration of Panoramic Hyperspectral Imagery with Photorealistic Lidar Models Aleksandra Sima, Simon J. Buckley, Tobias H. Kurz, Danilo Schneider Photogrammetrie - Fernerkundung - Geoinformation, Volume 2012, Number 4, August 2012 , pp. 443-454(12) This paper presents a method for increasing the automation of the registration of panoramic hyperspectral images with co-registered conventional digital imagery and a point cloud acquired with a terrestrial laser scanner (lidar), for geological purposes. The SIFT (scale invariant feature transform) interest operator is used to find homologous points between the two imagery types which, because they are recorded at different spectral ranges (visible and short wave infrared) using different geometric projections, differ significantly in appearance. After reducing false matches using RANSAC (random sample consensus), a geometric model for panoramic cameras is applied to retrieve the orientation parameters of the hyperspectral scenes. Once registered, hyperspectral classifications can be combined with the lidar geometry in photorealistic models, allowing material information to be linked to object geometry. Improved automation of the data registration reduces processing time and m
2012
The Effects of Spectral Pretreatments on Chemometric Analyses of Soil Profiles Using Laboratory Imaging Spectroscopy,

Hindawi Publishing Corporation, Applied and Environmental Soil Science, Volume 2012, Article ID 274903, 12 pages, doi:10.1155/2012/274903

The Effects of Spectral Pretreatments on Chemometric Analyses of Soil Profiles Using Laboratory Imaging Spectroscopy Henning Buddenbaum, Markus Steffens Hindawi Publishing Corporation, Applied and Environmental Soil Science, Volume 2012, Article ID 274903, 12 pages, doi:10.1155/2012/274903 Laboratory imaging spectroscopy can be used to explore physical and chemical variations in soil profiles on a submillimetre scale. We used a hyperspectral scanner in the 400 to 1000nm spectral range mounted in a laboratory frame to record images of two soil cores. Samples from these cores were chemically analyzed, and spectra of the sampled regions were used to train chemometric PLS regression models. With these models detailed maps of the elemental concentrations in the soil cores could be produced. Eight different spectral pretreatments were applied to the sample spectra and to the resulting images in order to explore the influence of these pre-treatments on the estimation of elemental concentrations. We found that spectral preprocessing has a minor influence on chemometry results when powerful regression algorithms like PLSR are used.
2012
Hyperspectral Anomaly Detection: Comparative Evaluation in Scenes with Diverse Complexity,

Hindawi Publishing Corporation, Journal of Electrical and Computer Engineering, Volume 2012, Article ID 162106, 16 pages, doi:10.1155/2012/162106

Hyperspectral Anomaly Detection: Comparative Evaluation in Scenes with Diverse Complexity Dirk C. Borghys, Ingebjørg Kåsen, Veronique Achard, Christiaan Perneel Hindawi Publishing Corporation, Journal of Electrical and Computer Engineering, Volume 2012, Article ID 162106, 16 pages, doi:10.1155/2012/162106 Anomaly detection (AD) in hyperspectral data has received a lot of attention for various applications. The aim of anomaly detection is to detect pixels in the hyperspectral data cube whose spectra differ significantly from the background spectra. Many anomaly detectors have been proposed in the literature. They differ in the way the background is characterized and in the method used for determining the difference between the current pixel and the background. The most well-known anomaly detector is the RX detector that calculates the Mahalanobis distance between the pixel under test (PUT) and the background. Global RX characterizes the background of the complete scene by a single multivariate normal probability density function. In many cases, this model is not appropriate for describing the background. For that reason a variety of other anomaly detection methods have been developed. This paper examines three classes of anomaly detectors: subspace methods, local methods, and segmentation-based methods. Representative examples of each class are chosen and applied on a set of hyperspectral data with diverse complexity. The results are evaluated and compared.
2012
Classification in High-dimensional Spectral Data – Precision vs. Interpretability vs. Model Size,

Workshop New Challenges in Neural Computation

Classification in High-dimensional Spectral Data – Precision vs. Interpretability vs. Model Size Andreas Backhaus, Udo Seiffert Workshop New Challenges in Neural Computation This paper evaluates aspects of precision, interpretability and model size of several computational intelligence based classification methods in the context of hyperspectral imaging and Raman spectroscopy. It is focussed on state-of-the-art representative paradigms of a number of different concepts, such as prototype based, kernel based, and support vector based approaches
2012
Combined airborne thermography and visible-to-near infrared reflectance measurement for soil moisture mapping,

11th International Conference on Quantitative InfraRed Thermography

Combined airborne thermography and visible-to-near infrared reflectance measurement for soil moisture mapping Jean-Claude Krapez, Christian Chatelard, Jean-François Nouvel, Philippe Déliot 11th International Conference on Quantitative InfraRed Thermography We first present a review of the so-called triangle/trapezoid method for soil moisture evaluation from optical remote sensing data obtained in the red, near infrared and thermal infrared bands. Recent improvements based on additional vegetation indexes obtained for example from multiwavelength signals in SWIR band will also be presented. In a second part we describe the results we obtained for this purpose by using a microbolometer camera onboard of a motorglider. Signal processing for atmosphere correction and orthorectification was specifically developed for this application. First results on the path for identification of soil water content with this approach will be presented.
2012
Segmentation of vegetation scenes: the SIEMS method,

Proc. SPIE 8537, Image and Signal Processing for Remote Sensing XVIII, 85371A (November 8, 2012); doi:10.1117/12.973705

Segmentation of vegetation scenes: the SIEMS method Alexandre Alakian Proc. SPIE 8537, Image and Signal Processing for Remote Sensing XVIII, 85371A (November 8, 2012); doi:10.1117/12.973705 This paper presents an unsupervised segmentation method dedicated to vegetation scenes with decametric or metric spatial resolutions. The proposed algorithm, named SIEMS, is based on the iterative use of the Expectation–Maximization algorithm and offers a good trade-off between oversegmentation and undersegmentation. Moreover, the choice of its input parameters is not image–dependent on the contrary to existing technics and its performances are not crucially determined by these input parameters. SIEMS consists in creating a coarse segmentation of the image by applying an edge detection method (typically the Canny–Deriche algorithm) and splitting iteratively the undersegmented areas with the Expectation–Maximization algorithm. The method has been applied on two images and shows satisfactory results. It notably allows to distinguish segments with slight radiometric variations without leading to oversegmentation.
2012
Modified Conn-Index for the evaluation of fuzzy clusterings,

ESANN 2012 proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Bruges (Belgium), 25-27 April 2012, i6doc.com publ., ISBN 978-2-87419-049-0.

Modified Conn-Index for the evaluation of fuzzy clusterings Tina Geweniger, Marika Kästner, Mandy Lange, Thomas Villmann ESANN 2012 proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Bruges (Belgium), 25-27 April 2012, i6doc.com publ., ISBN 978-2-87419-049-0. We propose an extension of the Conn-Index to evaluate fuzzy cluster solutions obtained from fuzzy prototype vector quantization, whereas the original Conn-Index was designed for crisp vector quantization models. The fuzzy index explicitly takes the fuzzy assignments resulting from fuzzy vector quantization into account. This avoids the information loss which would occur if the original crisp index is applied to fuzzy solutions
2012
Getting simultaneous red and near infrared bands from a single digital camera for plant monitoring applications,

CIGR-Ageng 2012. International Conference on Agricultural Engineering, Valencia : Spain

Getting simultaneous red and near infrared bands from a single digital camera for plant monitoring applications Gilles Rabatel, Nathalie Gorretta-Monteiro, Sylvian Labbé CIGR-Ageng 2012. International Conference on Agricultural Engineering, Valencia : Spain Multispectral images including red and near-infrared bands have proved their efficiency for vegetation-soil discrimination and agricultural monitoring in remote sensing applications. But they remain rarely used in ground and UAV imagery, due to a limited availability of adequate 2D imaging devices. In this paper, we propose and evaluate an original solution to obtain simultaneously the near-infrared and red bands from a standard RGB camera, after having removed the near-infrared blocking filter inside. First, the theoretical approach is described, as well as simulated results on a set of soil and vegetation luminance spectra with two different still cameras (Canon 500D and Sigma SD14). Then examples of images obtained in real field conditions are given, and compared with standard colour image acquisition for pixel-based plant/soil discrimination, using an automatic thresholding method. It appears that in most cases our new acquisition procedure brings a significative improvement, opening new opportunities for crop monitoring a
2012
Weeds-wheat discrimination using hyperspectral imagery,

CIGR-Ageng 2012. International Conference on Agricultural Engineering, 8-12 Juillet 2012, Valence, Espagne

Weeds-wheat discrimination using hyperspectral imagery Xavier Hadoux, Nathalie Gorretta-Monteiro, Gilles Rabatel CIGR-Ageng 2012. International Conference on Agricultural Engineering, 8-12 Juillet 2012, Valence, Espagne The difficulties to efficiently discriminate between weeds and crop by computer vision remains today a major obstacle to the promotion of localized weeding practices. The objective of the present study was to evaluate the potential of hyperspectral imagery for the detection of dicotyledonous weeds in durum wheat during weeding period (end of winter). An acquisition device based on a push-broom camera mounted on a motorized rail has been used to acquire top-view images of crop at a distance of one meter. A reference surface set in each image, as well as specific spectral pre-processing, allow overcoming variable outdoor lighting conditions. Spectral discrimination between weeds and crop, obtained by PLS-LDA, appears quite efficient, with a 8% prediction error on an independent test set.
2012
Comparative evaluation of hyperspectral anomaly detection methods in scenes with diverse complexity,

OECD Conference Center, Paris, France / 8–10 February

Comparative evaluation of hyperspectral anomaly detection methods in scenes with diverse complexity Dirk C. Borghys, Ingebjørg Kåsen, Veronique Achard, Christiaan Perneel OECD Conference Center, Paris, France / 8–10 February Anomaly detection in hyperspectral data has received a lot of attention for various applications and is especially important for defence and security. The aim of anomaly detection is to detect pixels in the hyperspectral data cube whose spectra differ significantly from the background spectra. Many types of anomaly detectors have been proposed in literature. They differ by the way the background spectra are defined and described and by the method used for determining the difference between the pixel under test and the estimated background characteristics. The most well-known anomaly detector is the RX detector. Several detectors have been derived from the basic RX detector. On the other hand methods based on image segmentation have also been introduced. These are particularly useful in areas characterised by a highly structured background (e.g. urban scenes). The current paper presents a comparison of the results obtained by representative examples of two classes of anomaly detector: the RX-family of detectors and the segmentation-based detectors.
2012
Integration of reflectances and thermography imagery for transport infrastructures diagnostics,

Geophysical Research Abstracts, Vol. 14, EGU2012-9656, 2012, EGU General Assembly

Integration of reflectances and thermography imagery for transport infrastructures diagnostics Stefano Pignatti, Angelo Palombo, Simone Pascucci, Frederico Santini Geophysical Research Abstracts, Vol. 14, EGU2012-9656, 2012, EGU General Assembly The integrated use of reflectances and thermography to study and diagnostic of transport infrastructures has been applied on the Musumeci Bridge (Potenza, Italy) test site as a fast and non-destructive tool in the framework of the Integrated System for Transport Infrastructures surveillance and Monitoring by Electromagnetic Sensing (ISTIMES) project, funded by the European Commission in the frame of a joint Call “ICT and Security” of the Seventh Framework Programme, in order to extract appropriate information and make useful decisions
2012
Mapping the distribution of chemical properties in soil profiles using laboratory imaging spectroscopy, SVM and PLS regression,

EARSeL eProceedings 11, 1/2012

Mapping the distribution of chemical properties in soil profiles using laboratory imaging spectroscopy, SVM and PLS regression Henning Buddenbaum, Markus Steffens EARSeL eProceedings 11, 1/2012 Laboratory imaging spectroscopy as a tool for studying the three-dimensional properties of soils is introduced. Hyperspectral images of parallel slices of a soil core sampled in a custom-made steel box were made. We used image spectra from chemically analysed samples to train Support Vector Machine and Partial Least Squares regression models of chemical soil properties. Special attention has to be paid on the correct number of estimator variables. The models were applied on the images to create sub-millimetre scale maps of carbon, nitrogen, iron, aluminium and manganese content in the soil profiles.
2012
Nonlinear spectral unmixing of hyperspectral images using Gaussian processes,

TECHNICAL REPORT – 2012, July, University of Toulouse, IRIT/INP-ENSEEIHT, 2 rue Camichel, BP 7122, 31071 Toulouse cedex 7, France

Nonlinear spectral unmixing of hyperspectral images using Gaussian processes Yoann Altmann, Nicolas Dobigeon, Steve McLaughlin, Jean-Yves Tourneret TECHNICAL REPORT – 2012, July, University of Toulouse, IRIT/INP-ENSEEIHT, 2 rue Camichel, BP 7122, 31071 Toulouse cedex 7, France This paper presents an unsupervised algorithm for nonlinear unmixing of hyperspectral images. The proposed model assumes that the pixel reflectances result from a nonlinear function of the abundance vectors associated with the pure spectral components. We assume that the spectral signatures of the pure components and the nonlinear function are unknown. The first step of the proposed method consists of the Bayesian estimation of the abundance vectors for all the image pixels and the nonlinear function relating the abundance vectors to the observations. The endmembers are subsequently estimated using Gaussian process regression. The performance of the unmixing strategy is evaluated with simulations conducted on synthetic and real data.
2012
Hardware accelerated real time classification of hyperspectral imaging data for coffee sorting,

ESANN 2012 proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Bruges (Belgium), 25-27 April 2012, i6doc.com publ., ISBN 978-2-87419-049-0. Available from http://www.i6doc.com/en/livre/?GCOI=28001100967420.

Hardware accelerated real time classification of hyperspectral imaging data for coffee sorting Andreas Backhaus, Jan Lachmair, Ulrich Rückert, Udo Seiffert ESANN 2012 proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Bruges (Belgium), 25-27 April 2012, i6doc.com publ., ISBN 978-2-87419-049-0. Available from http://www.i6doc.com/en/livre/?GCOI=28001100967420. Hyperspectral imaging has been proven to be a viable tool for automated food inspection that is non-invasive and on-line capable. In this contribution a hardware implemented Self-Organizing Feature Map with Conscience (CSOM) is presented that is capable of on-line adaptation and recall in order to learn to classify green coffee varieties as well as coffee of different roast stages. The CSOM showed favourable results in some datasets compared to a number of classical supervised neural network classifiers. The massive parallel neural hardware architecture allows for constant processing times at different map sizes.
2012
Close range hyperspectral imaging integrated with terrestrial lidar scanning applied to rock characterisation at centimetre scale,

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B5, 2012 XXII ISPRS Congress, 25 August – 01 September 2012, Melbourne, Australia

Close range hyperspectral imaging integrated with terrestrial lidar scanning applied to rock characterisation at centimetre scale Tobias H. Kurz, Simon J. Buckley, John A. Howell International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B5, 2012 XXII ISPRS Congress, 25 August – 01 September 2012, Melbourne, Australia Compact and lightweight hyperspectral imagers allow the application of close range hyperspectral imaging with a ground based scanning setup for geological fieldwork. Using such a scanning setup, steep cliff sections and quarry walls can be scanned with a more appropriate viewing direction and a higher image resolution than from airborne and spaceborne platforms. Integration of the hyperspectral imagery with terrestrial lidar scanning provides the hyperspectral information in a georeferenced framework and enables measurement at centimetre scale. In this paper, three geological case studies are used to demonstrate the potential of this method for rock characterisation. Two case studies are applied to carbonate quarries where mapping of different limestone and dolomite types was required, as well as measurements of faults and layer thicknesses from inaccessible parts of the quarries. The third case study demonstrates the method using artificial lighting, applied in a subsurface scanning scenario where solar radiation cannot be utilised.
2012
Sorting of recycled glass by Hyper Spectral Imaging,

Glass Trend Seminar, Alternative Raw materials and Advanced Batch Pretreatments for glass melting, October 18 - 19, 2012, Eindhoven, the Netherlands

Sorting of recycled glass by Hyper Spectral Imaging Mathi Rongen, Ivar Baarstad, Julio Ernesto Hernández Palacios, Trond Løke Glass Trend Seminar, Alternative Raw materials and Advanced Batch Pretreatments for glass melting, October 18 - 19, 2012, Eindhoven, the Netherlands Problems of glass-ceramics: Glass-ceramic pieces (especially > 3 mm) entering the furnace can cause serious production problems: Interruption of the forming process by cutting problems Damages of the shear blade Glass defects (knots/cords)
2012
Airborne VNIR-SWIR hyperspectral remote sensing for environmental urban mapping,

Telecom Bretagne 2012

Airborne VNIR-SWIR hyperspectral remote sensing for environmental urban mapping Patrick Launeau, Zeineb Kassouk, Patrice Mestayer Telecom Bretagne 2012
2012
Remote sensing of aquatic and palustral invasive plants: The case of Ludwigia grandiflora (water primrose),

NEREUS , Saint-Malo, june 1, 2012

Remote sensing of aquatic and palustral invasive plants: The case of Ludwigia grandiflora (water primrose) Hervé Nicolas, Elise Athané, Jacques Haury, Benjamin Bottner NEREUS , Saint-Malo, june 1, 2012 Contamination of the Vilaine basin since 1980 Extension in streams (shallow with little current) Accelerated development related to water quality (nitrate phosphorus) Rapid eutrophication of the environment (biodiversity, usage)
2012
Hyperspectral image analysis of different carbonate lithologies (limestone, karst and hydrothermal dolomites): the Pozalagua Quarry case study (Cantabria, North-west Spain),

Sedimentology, 59(2): 623-645. doi:10.1111/j.1365-3091.2011.__01269.x.

Hyperspectral image analysis of different carbonate lithologies (limestone, karst and hydrothermal dolomites): the Pozalagua Quarry case study (Cantabria, North-west Spain) Tobias H. Kurz, Julie Dewit, Simon J. Buckley, John B. Thurmond, David W. Hunt, Rudy Swennen Sedimentology, 59(2): 623-645. doi:10.1111/j.1365-3091.2011.__01269.x. Ground-based hyperspectral imaging combined with terrestrial lidar scanning is a novel technique for outcrop analysis, which has been applied to Early and Late Albian carbonates of the Pozalagua Quarry (Cantabrian Mountains, Spain). An image processing workflow has been developed for differentiating limestone from dolomite, providing additional sedimentary and diagenetic information, and the possibility to quantitatively delineate diagenetic phases in an accurate way. Spectral absorption signatures can be linked to specific sedimentary or diagenetic products, such as recent and palaeokarst, hydrothermal karst, (solution enlarged) fractures and different dolomite types. Some of the spectral signatures are related to iron, manganese, organic matter, clay and/or water content. Ground-truthing accessible parts of the quarry showed that the classification based on hyperspectral image interpretation was very accurate. This technique opens the possibility for quantitative data evaluation on sedimentary and diagenetic features in inaccessible outcrops. This study demonstrates the potential of ground-based imaging spectroscopy to provide information about the chemical–mineralogical distribution in outcrops, which could otherwise not be established using conventional field methods.
2012
A simple quadratic method of absorption feature wavelength estimation in continuum removed spectra,

Remote Sensing of Environment, Volume 118, 15 March 2012, Pages 273-283, ISSN 0034-4257, 10.1016/j.rse.2011.11.025.(http://www.sciencedirect.com/science/article/pii/S0034425711004226)

A simple quadratic method of absorption feature wavelength estimation in continuum removed spectra Andrew Rodger, Carsten Laukamp, Maarten Haest, Thomas Cudahy Remote Sensing of Environment, Volume 118, 15 March 2012, Pages 273-283, ISSN 0034-4257, 10.1016/j.rse.2011.11.025.(http://www.sciencedirect.com/science/article/pii/S0034425711004226) A simple quadratic method is proposed for estimating the wavelengths of absorption features in the short wave infrared spectral region from hyperspectral instruments ranging from 2 to 18 nm sampling intervals. The method uses a direct substitution of the three spectral reflectance bands to achieve an estimate of the wavelength of the point of maximum absorption. The method is shown to be stable across different sampling regimes and therefore across different hyperspectral instruments. The results show it is possible to accurately estimate the wavelength of spectral absorption features to an RMSE of ±3.8 nm in the 2000–2500 nm spectral region over multiple sampling intervals and resolutions in sensors with signal-to-noise greater than 500:1.
2012
Hyperspectral Imaging of Bruises in the SWIR Spectral Region,

Proc. SPIE Photonic West BIOS, San Francisco, USA, Jan. 21-26, 2012.

Hyperspectral Imaging of Bruises in the SWIR Spectral Region Lise Randeberg, Julio Ernesto Hernández Palacios Proc. SPIE Photonic West BIOS, San Francisco, USA, Jan. 21-26, 2012. Optical diagnostics of bruised skin might provide important information for characterization and age determination of such injuries. Hyperspectral imaging is one of the optical techniques that have been employed for bruise characterization This technique combines high spatial and spectral resolution and makes it possible to study both chromophore signatures and -distributions in an injury. Imaging and spectroscopy in the visible spectral range have resulted in increased knowledge about skin bruises. So far the SWIR region has not been explored for this application The main objective of the current study was to characterize bruises in the SWIR wavelength range. Hyperspectral images in the SWIR (900-2500nm ) and VIS (400-850nm) spectral range were collected from 3 adult volunteers with bruises of known age. Data were collected over a period of 8 days. The data were analyzed using spectroscopic techniques and statistical image analysis. Preliminary results from the pilot study indicate that SWIR hyperspectral imaging might be an important supplement to imaging in the visible part of the spectrum. The technique emphasizes local edema and gives a possibility to visualize bruises that cannot easily be seen in the visible part of the spectrum.
2011
Robust classification of the nutrition state in crop plants by hyperspectral imaging and artificial neural networks,

Proc. 3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2011

Robust classification of the nutrition state in crop plants by hyperspectral imaging and artificial neural networks Andreas Backhaus, Felix Bollenbeck, Udo Seiffert Proc. 3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2011
2011
Relevance Learning in Unsupervised Vector Quantization Based on Divergences Advances in Self-Organizing Maps,

8th International Workshop, WSOM 2011, 6731, 90-100

Relevance Learning in Unsupervised Vector Quantization Based on Divergences Advances in Self-Organizing Maps Marika Kästner, Andreas Backhaus, Tina Geweniger, S. Haase, Udo Seiffert, Thomas Villmann 8th International Workshop, WSOM 2011, 6731, 90-100
2011
High-Throughput Quality Control of Coffee Varieties and Blends by Artificial Neural Networks from Hyperspectral Imaging,

Proceedings of the 1st International Congress on Cocoa, Coffee and Tea (CoCoTea), 2011, 1, 88-92

High-Throughput Quality Control of Coffee Varieties and Blends by Artificial Neural Networks from Hyperspectral Imaging Andreas Backhaus, Felix Bollenbeck, Udo Seiffert Proceedings of the 1st International Congress on Cocoa, Coffee and Tea (CoCoTea), 2011, 1, 88-92
2011
Ground-based hyperspectral and lidar scanning: a complementary method for geoscience research,

International Association of Mathematical Geosciences Conference, 5-9th September, Salzburg, Austria.

Ground-based hyperspectral and lidar scanning: a complementary method for geoscience research Tobias H. Kurz, Simon J. Buckley, Danilo Schneider, Aleksandra Sima, John A. Howell International Association of Mathematical Geosciences Conference, 5-9th September, Salzburg, Austria.
2011
Hyperspectral Imaging Technology and Systems, Exemplified by Airborne Real-time Target Detection,

Proc. Conference on Lasers and Electro-Optics

Hyperspectral Imaging Technology and Systems, Exemplified by Airborne Real-time Target Detection Torbjørn Skauli, Trym V. Haavardsholm, Ingebjørg Kåsen, Thomas Olsvik Opsahl, Amela Kavara, Atle Skaugen Proc. Conference on Lasers and Electro-Optics
2011
Imaging Spectrometry of Meteorite Samples Relevant to Vesta and the Moon.,

42nd Lunar and Planetary Science Conference (2011)

Imaging Spectrometry of Meteorite Samples Relevant to Vesta and the Moon. J.-Ph. Combe, S. Le Mouélic, Patrick Launeau, A. Irving, T. B. McCord 42nd Lunar and Planetary Science Conference (2011) The interpretation of remote reflectance spectra of planetary surfaces relies on reference spectra of known mineralogical composition, analogs, or samples when available. Some meteorites are also associated to rocky celestial bodies. The lunar origin of some meteorites has been proven by their equivalence to samples from the Moon. Howardite, eucrite and diogenites meteorites (HED) are assumed to come from Vesta because of similarities between their reflectance spectra. Meteorite samples are generally breccias of heterogeneous composition which full characterization implies either statistical analysis over many subsets, or imaging and mapping. Quantitative abundances are estimated at micrometric scales only, or by averaging. Imagery of samples is usually performed as a guide for microprobing. Recent developments of reflectance imaging spectrometry in the laboratory allow now for compositional mapping of thick samples, which is a non-destructive technique. The other advantage is the possibility of using the same technique on samples (in the laboratory or insitu) and on planetary surfaces (from orbit or from ground-based observations}, therefore making comparative interpretation more direct and more reliable. Finally, this is an opportunity for developing and test methods of spectral analysis against composition derived from chemical analysis. Such cross-analyses are support for data processing of past and future missions. This study started in the context of the mission of the Moon Mineralogy Mapper (M3) [1] onboard Chandrayaan-1, as well as future observations of Vesta by the Visible and Infrared spectrometer (VIR) onboard Dawn [2]. We present the first results of spectral mixture analysis on lunar meteorites and on HEDs.
2011
High Resolution Airborne Hyperspectral Data for Mapping of Ramin Distribution in Peat Swamp Forest,

Forest Research Institute Malaysia, International Tropical Timber Organization and Convention on International Trade in Endangered Species of Wild Fauna and Flora 2011

High Resolution Airborne Hyperspectral Data for Mapping of Ramin Distribution in Peat Swamp Forest F. Mohd Azahari, H. Khali Aziz, O. Hamdan Forest Research Institute Malaysia, International Tropical Timber Organization and Convention on International Trade in Endangered Species of Wild Fauna and Flora 2011
2011
SPECTRAL POLISHING OF HIGH RESOLUTION IMAGING SPECTROSCOPY DATA,

7th SIG-IS Workshop on Imaging Spectroscopy, Edinburgh, pp. 7.

SPECTRAL POLISHING OF HIGH RESOLUTION IMAGING SPECTROSCOPY DATA Daniel Schläpfer, Rudolf Richter 7th SIG-IS Workshop on Imaging Spectroscopy, Edinburgh, pp. 7. Imaging spectroscopy systems covering the visible to the short wave infrared range at wavelength resolutions below 10 nm are more and more used for research and for environmental applications. The compensation for influences of the atmosphere is well solved by inversion of radiative transfer codes as it is done by the ATCOR model or similar methods. However, spectral artifacts remain visible after the atmospheric correction. Current hyperspectral systems such as HySpex, AISA or APEX resolve the spectrum at sampling intervals down to 1-2 nm. Artifacts are usually visible in such data even after optimal correction for spectral smile distortions. The final correction for such artifacts is known as 'spectral polishing'. A variety methods of spectral polishing are tested on sample data sets of the Hyperion and the HySpex imaging spectrometer. Additionally, simulations on artificial data show tradeoffs between information preservation and noise removal in the spectral polishing process. Based on this evaluation, recommendations are given on how to improve spectra by polishing techniques for both coarse and high resolution data. It is then shown, how such techniques are to be included as standard processing steps in higher level data processing chains.
2011
Mapping ash tree colonization in an agricultural mountain landscape: Investigating the potential of hyperspectral imagery,

Geoscience and Remote Sensing Symposium (IGARSS), 2011 IEEE International

Mapping ash tree colonization in an agricultural mountain landscape: Investigating the potential of hyperspectral imagery David Sheeren, Mathieu Fauvel, Sylvie Ladet, Anne Jacquin, Georges Bertoni, Annick Gibon Geoscience and Remote Sensing Symposium (IGARSS), 2011 IEEE International In this contribution, we evaluate the potential of hyperspectral imagery for identifying ash tree and other dominant species in encroached mountain grasslands. The method is based on a supervised approach using Support Vector Machines in which kernel parameters are fixed by kernel alignment. We present the application of the method and the first results obtained. The statistical measures derived from the confusion matrix show that tree species are well discriminated with accuracies >; 90%. These results confirm the possibility of detecting tree species with this data and the performance of the SVM classifier.
2011
Comparación de índices ópticos de imágenes hiperespectrales en relación con madurez de melocotón: capacidad de detección y robustez,

VI Congreso Iberico de AgroIngenieria

Comparación de índices ópticos de imágenes hiperespectrales en relación con madurez de melocotón: capacidad de detección y robustez Lourdes Lleó, Jean-Michel Roger, Ana Herrero-Langreo, Belen Diezma-Iglesias, Pilar Barreiro, Margarita Ruiz-Altisent VI Congreso Iberico de AgroIngenieria The present research is focused on the application of artificial vision to assess the ripening of red skinned softflesh peach (‘Richlady’). Artificial vision allows a spatially detailed determination of the ripening stage of the fruit. The considered optical indexes (Ind1 and Ind2, proposed in the present research, and Ind3 and IAD, proposed by other authors) are based on the combination of wavelengths close to the chlorophyll absorption peak at 680 nm. Ind1 corresponds approximately to the depth of the absorption peak, and Ind2 corresponds to the relative absorption peak. An artificial image of each index was obtained by computing the corresponding reflectance images, which were acquired with a hyperspectral camera. All indexes were able to correct convexity (except for the just-harvested peaches and for Ind1). Ind2 is the preferred index; it showed the highest discriminating power between ripening stages and no influence of convexity. Ind2 also allowed the differentiation of ripening regions within the fruits, and it showed the evolution of those regions during ripening
2011
A Constrained Band Selection Method Based on Information Measures for Spectral Image Color Visualization,

IEEE Transactions on Geoscience and Remote Sensing PP, 99 (2011) 1-12, DOI : 10.1109/TGRS.2011.2158319

A Constrained Band Selection Method Based on Information Measures for Spectral Image Color Visualization Steven Le Moan, Alamin Mansouri, Yvon Voisin, Jon Yngve Hardeberg IEEE Transactions on Geoscience and Remote Sensing PP, 99 (2011) 1-12, DOI : 10.1109/TGRS.2011.2158319 We present a new method for the visualization of spectral images, based on a selection of three relevant spectral channels to build a Red-Green-Blue composite. Band selection is achieved by means of information measures at the first, second and third orders. Irrelevant channels are preliminarily removed by means of a center-surround entropy comparison. A visualization-oriented spectrum segmentation based on the use of color matching functions allows for computational ease and adjustment of the natural rendering. Results from the proposed method are presented and objectively compared to four other dimensionality reduction techniques in terms of naturalness and informative content
2011
Evaluation of the sub-pixel performance of anomaly detectors,

3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)

Evaluation of the sub-pixel performance of anomaly detectors Dirk C. Borghys, Christiaan Perneel, Veronique Achard, Ingebjørg Kåsen 3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS) Anomaly detection in hyperspectral data has received much attention for various applications and is especially important for defense and security applications. Anomaly detection detects pixels in the hyperspectral data cube whose spectra differ significantly from the background spectra. Most existing methods estimate the spectra of the (local or global) background and then detect anomalies as pixels with a large spectral distance w.r.t. the determined background spectra. Many types of anomaly detectors have been proposed in literature. The most well-known anomaly detector is the RX detector that calculates the Mahalanobis distance between the pixel under test and the background. This paper investigates the sub-pixel detection performance of two classes of anomaly detectors: the family of RX-based detectors and the segmentation-based anomaly detectors. Representative examples of each class are selected and results obtained on three different datacubes are analyzed
2011
Integrated optical and thermal data analysis for a rapid surface diagnostic of transport infrastructures: the cement beam case study in Montagnole (France),

Geophysical Research Abstracts, Vol. 13, EGU2011-9867, 2011, EGU General Assembly 2011

Integrated optical and thermal data analysis for a rapid surface diagnostic of transport infrastructures: the cement beam case study in Montagnole (France) Simone Pascucci, Angelo Palombo, Cristiana Bassani, Rosa Maria Cavalli, Frederico Santini, Stefano Pignatti Geophysical Research Abstracts, Vol. 13, EGU2011-9867, 2011, EGU General Assembly 2011 The integrated use of hyperspectral (0.4-1.0 micron) and high sensitivity thermal camera data for surface diagnostics of transport infrastructures is a challenging investigation tool that can be combined with other non-destructive penetrating techniques (e.g. GPR) in order to acquire actual information on infrastructure status to prioritize the intervention areas to be maintained
2011
Carbonate Mineral mapping and Geologic Outcroup Modelling using Hyperspectral in the Agadir basin targeting the Jurassic sequence, Western High Atlas, Morocco,

AAPG Search and Discovery Article #90137©AAPG European Region’s 2nd International Conference held in Marrakech, Morocco, 5-7 October 2011.

Carbonate Mineral mapping and Geologic Outcroup Modelling using Hyperspectral in the Agadir basin targeting the Jurassic sequence, Western High Atlas, Morocco Brahim Ouajhain, Kamal Labbassi, Patrick Launeau, Rachid Baissa, Haddou Jabour, Anne Gaudin, Patrick Pinet AAPG Search and Discovery Article #90137©AAPG European Region’s 2nd International Conference held in Marrakech, Morocco, 5-7 October 2011. Hyperspectral imaging is a proven technology used for identifying and mapping minerals based on their reflectance or emissivity signatures. Hyspex allows direct identification of carbonate minerals such as calcite, dolomite, ankerite and siderite in the visible/near infrared (VNIR); clays and sulfates, and other minerals in the short wave infrared (SWIR); The unique capability of imaging spectrometry to produce detailed maps of the spatial distribution of specific minerals (carbonates in this case), mineral assemblages, and mineral variability on the Agadir basin during the Jurassic makes it an ideal tool for enhanced geomorphic mapping. Imaging spectrometry, used in conjunction with complimentary datasets such as Light Detection and Ranging (LiDAR), or Digital Elevation Model (DEM), provides a unique means of visualizing the spatial distribution and association of mineralogy with topography, thus contributing to the understanding of the relationship between geology and landscape and to improved interpretation of surface geologic processes.A site in the Imouzzar anticline is used to illustrate the basic results of mineral mapping for characterization of dolomitization systems and exploration of all minerals species. Jurassic bedrock in the area consists of limestones, dolomites, marls, evaporites and sandstones. A variety of minerals, including calcite, dolomite, kaolinite, illite and gypsum were mapped in these systems and verified on the ground. The analysis approach uses extraction of spectral signatures and map specific minerals and mineral assemblages exposed at the surface of each sample extracted from different Jurassic formations from Liassic to the Kimmeridgian.
2011
Comparison of multispectral indexes extracted from hyperspectral images for the assessment of fruit ripening,

Journal of Food Engineering, Volume 104, Issue 4, June 2011, Pages 612–620

Comparison of multispectral indexes extracted from hyperspectral images for the assessment of fruit ripening Lourdes Lleó, Jean-Michel Roger, Ana Herrero-Langreo, Belen Diezma-Iglesias, Pilar Barreiro Journal of Food Engineering, Volume 104, Issue 4, June 2011, Pages 612–620 The present research is focused on the application of artificial visión to assess the ripening of red skinned soft-flesh peach ('Richlady'). Artificial visión allows a spatially detailed determination of the ripening stage of the fruit. The considered optical indexes (Indi and Ind2, proposed in the present research, and Ind3 and IAD, proposed by other authors) are based on the combination of wavelengths cióse to the chlorophyll absorption peak at 680 nm. Ind} corresponds approximately to the depth of the absorption peak, and Ind2 corresponds to the relative absorption peak. An artificial image of each Índex was obtained by computing the corresponding reflectance images, which were acquired with a hyperspectral camera. All indexes were able to correct convexity (except for the just-harvested peaches and for Ind}). Ind2 is the preferred Índex; it showed the highest discriminating power between ripening stages and no influence of convexity. Ind2 also allowed the differentiation of ripening regions within the fruits, and it showed the evolution of those regions during ripening.
2011
Spatially variant dimensionality reduction for the visualization of multi/hyperspectral images,

International Conference on Image Analysis and Recognition, Burnaby : Canada (2011), DOI : 10.1007/978-3-642-21593-3_38

Spatially variant dimensionality reduction for the visualization of multi/hyperspectral images Steven Le Moan, Alamin Mansouri, Yvon Voisin, Jon Yngve Hardeberg International Conference on Image Analysis and Recognition, Burnaby : Canada (2011), DOI : 10.1007/978-3-642-21593-3_38 In this paper, we introduce a new approach for color visualization of multi/hyperspectral images. Unlike traditional methods, we propose to operate a local analysis instead of considering that all the pixels are part of the same population. It takes a segmentation map as an input and then achieves a dimensionality reduction adaptively inside each class of pixels. Moreover, in order to avoid unappealing discontinuities between regions, we propose to make use of a set of distance transform maps to weigh the mapping applied to each pixel with regard to its relative location with classes’ centroids. Results on two hyperspectral datasets illustrate the efficiency of the proposed method.
2011
Potential of field hyperspectral imaging as a non destructive method to assess leaf nitrogen content in Wheat,

Field Crops Research 122, 1 (2011) p. 25 - p. 31

Potential of field hyperspectral imaging as a non destructive method to assess leaf nitrogen content in Wheat Nathalie Vigneau, Martin Ecarnot, Gilles Rabatel, Pierre Roumet Field Crops Research 122, 1 (2011) p. 25 - p. 31 Nitrogen is the most important crop limiting factor, thus plant nitrogen status during plant cycle is a key parameter for crop monitoring. Many new techniques, based on leaf optical properties have been proposed for a nondestructive diagnosis to replace Nitrogen Nutrition Index which is a costly and destructive method. We intend here to study leaf nitrogen concentration accessibility from reflectance (400-1000 nm) spectra of whole plants from a field hyperspectral imaging set-up including difficulties related to variablesolar lighting and potential specular reflexion. Firstly, we calibrated a chemometrical model between leaf nitrogen concentration and reflectance spectra of flat leaves (R2=0.903, SEP=0.327 %DM), which validated the sensor and our reflectance correction process. As a second step, we calibrated a chemometrical model between nitrogen concentration and reflectance spectra of individual leaves from isolated plants grown in pots in greenhouse (R2=0.889, SEP=0.481 %DM) or under field conditions (R2=0.881, SEP=0.366 %DM). Pooling the two datasets provided us a relevant model to predict leaf nitrogen content for the two culture conditions (R2=0.875, SEP=0.496 %DM) suggesting that this technique is promising to assess nitrogen plant parameters with a non destructive method. This tool could be used to follow-up plant nitrogen dynamics criteria or to generate nitrogen spatial cartographies
2011
Getting NDVI Spectral Bands from a Single Standard RGB Digital Camera: A Methodological Approach,

14th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2011, La Laguna: Spain (2011)

Getting NDVI Spectral Bands from a Single Standard RGB Digital Camera: A Methodological Approach Gilles Rabatel, Nathalie Gorretta-Monteiro, Sylvian Labbé 14th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2011, La Laguna: Spain (2011) Multispectral images including red and near-infrared bands have proved their efficiency for vegetation-soil discrimination and agricultural monitoring in remote sensing applications. But they remain rarely used in ground and UAV imagery, due to a limited availibility of adequate 2D imaging devices. In this paper, a generic methodology is proposed to obtain simultaneously the near-infrared and red bands from a standard RGB camera, after having removed the near-infrared blocking filter inside. This method has been applied with two new generation SLR cameras (Canon 500D and Sigma SD14). NDVI values obtained from these devices have been compared with reference values for a set of soil and vegetation luminance spectra. The quality of the results shows that NDVI bands can now be acquired with high spatial resolution 2D imaging devices, opening new opportunities for crop monitoring applications.
2011
From the land to the sea: seamless cartography of coastal algae using airborne hyperspectral remote sensing,

Proceedings, 7th EARSeL Workshop on Imaging Spectroscopy, Edinburgh, Scotland, 11th – 13th April, 2011

From the land to the sea: seamless cartography of coastal algae using airborne hyperspectral remote sensing Guillaume Sciot, Marc Lennon, Sébastien Smet, Pascal Kohaut Proceedings, 7th EARSeL Workshop on Imaging Spectroscopy, Edinburgh, Scotland, 11th – 13th April, 2011 During spring and summer in areas which attract tourists, deposits of algae with tides on recreational beaches have to be managed on a daily basis. The access to spatial information on the algae is critical for management including gathering, namely: where, what kind, how much, which physiological state, where do they come from, location of stocks in the water, etc. A multitemporal and spatial point of view of the parameters is thus critical for managers, from the deposits on the shore to the stocks on the seafloor into the water. A methodology is proposed to elaborate such a seamless cartography of algae from the land to the sea. Using specific spectral features of water, the shoreline is estimated, allowing a mask of submerged areas to be built. Data are calibrated into reflectance above the surface and the inversion of the semi-analytical Lee model allows the bottom reflectance to be estimated, thus resulting in a seamless datacube of the ground, from the emerged area to the shallow water area. Spectral analysis methods are developed to discriminate the types of algae (red, green brown), their physiological state, and cover rate. All the parameters are derived from the seamless datacube using a single spectral library acquired on the shore, thus avoiding the need for doing spectral measurements into the water. This is clearly a practical and operational methodology for materials that are present both in the intertidal and nearshore areas. Moreover, the results confirm that water column correction is a relevant operation for coastal zone studies. The methodology developed is quite general, and is applied on a regional basis for the management of several tens of beaches in south French Britanny.
2011
Laboratory imaging spectroscopy applied to a complete soil profile,

Proceedings EARSel 7th SIG-Imaging Spectroscopy Workshop Imaging Spectroscopy Workshop, Edinburgh, 11-13 April 2011

Laboratory imaging spectroscopy applied to a complete soil profile Markus Steffens, Henning Buddenbaum Proceedings EARSel 7th SIG-Imaging Spectroscopy Workshop Imaging Spectroscopy Workshop, Edinburgh, 11-13 April 2011 Most analytical techniques in soil science are destructive - only limited number of analyses is possible until sample is lost => Bidirectional reflectance in VIS-NIR contains information on many parameters • In most studies bulk samples are taken and ground for further analyses • Soils are characterised by homogeneous, diagnostic horizons • But small-scale processes change elemental concentrations and introduce heterogeneities important for sorption, stabilisation etc. => Imaging spectroscopy adds spatial distribution to spectral information A hyperspectral camera (designed for airborne application) was used to... 1. Characterise the spatial homogeneity; 2. Discriminate diagnostic horizons and homogeneous areas; and 3. Predict elemental concentrations of C, N, Fe and Mn with a high spatial resolution for a whole soil profile.
2011
Biomass estimation by hyperspectral remote sensing : toward mapping of microphytobenthos productivity in the intertidal zones,

Proceedings EARSel 7th SIG-Imaging Spectroscopy Workshop Imaging Spectroscopy Workshop, Edinburgh, 11-13 April 2011

Biomass estimation by hyperspectral remote sensing : toward mapping of microphytobenthos productivity in the intertidal zones Farzaneh Kazemipour, Patrick Launeau, Vona Meleder Proceedings EARSel 7th SIG-Imaging Spectroscopy Workshop Imaging Spectroscopy Workshop, Edinburgh, 11-13 April 2011
2011
Integration of panoramic hyperspectral imaging with terrestrial lidar data.,

The Photogrammetric Record, Volume 26, Issue 134, pages 212–228, June 2011

Integration of panoramic hyperspectral imaging with terrestrial lidar data. Tobias H. Kurz, Simon J. Buckley, John A. Howell, Danilo Schneider The Photogrammetric Record, Volume 26, Issue 134, pages 212–228, June 2011 In many close-range applications it is essential to obtain information about the geometry of the target surface as well as its chemical composition. In this study, close-range hyperspectral imaging was integrated with terrestrial laser scanning to provide mineral and chemical information for geological field studies. The spectral data was collected with the HySpex SWIR-320m sensor, which operates in the infrared spectrum between the wavelengths of 1·3 and 2·5 μm. This sensor permits surfaces to be imaged with high spectral resolution, allowing detailed classification and analysis to be carried out. Photogrammetric processing of the hyperspectral imagery was achieved using an existing geometric model for rotating linear-array-based panoramic cameras. Bundle block adjustment of multiple images resulted in the registration of the spectral images in the lidar coordinate system, with a precision of around one image pixel. Although the image and control point network was not optimised for photogrammetric processing, it was possible to recover the exterior camera orientations, as well as additional camera calibration parameters. With the known image orientations, 3D lidar models could be textured with hyperspectral classifications, and the quality of the registration determined. The integration of the hyperspectral image products with the terrestrial lidar data enabled data interpretation and evaluation in a real-world coordinate system, and provided a reliable means of linking material and geometric information.
2011
Low-light hyperspectral imager for characterization of biological samples based on an sCMOS image sensor,

Proc. SPIE Photonic West BIOS, San Francisco, USA, Jan. 22-27, 2011

Low-light hyperspectral imager for characterization of biological samples based on an sCMOS image sensor Julio Ernesto Hernández Palacios, Lise Randeberg, Ingvild Johanne Haug, Ivar Baarstad, Trond Løke, Torbjørn Skauli Proc. SPIE Photonic West BIOS, San Francisco, USA, Jan. 22-27, 2011 The new "scientific CMOS" (sCMOS) sensor technology has been tested for use in hyperspectral imaging. The sCMOS offers extremely low readout noise combined with high resolution and high speed, making it attractive for hyperspectral imaging applications. A commercial HySpex hyperspectral camera has been modified to be used in low light conditions integrating an sCMOS sensor array. Initial tests of fluorescence imaging in challenging light settings have been performed. The imaged objects are layered phantoms labelled with controlled location and concentration of fluorophore. The camera has been compared to a state of the art spectral imager based on CCD technology. The image quality of the sCMOS-based camera suffers from artifacts due to a high density of pixels with excessive noise, attributed to the high operating temperature of the array. Image processing results illustrate some of the benefits and challenges of the new sCMOS technology.
2011
Hyperspectral imaging of atherosclerotic plaques in vitro,

Journal of Biomedical Optics 16(2), 026011 (February 2011)

Hyperspectral imaging of atherosclerotic plaques in vitro Eivind Larsen, Lise Randeberg, Elisabeth Olstad, Olav A. Haugen, Astrid Aksnes, Lars Svaasand Journal of Biomedical Optics 16(2), 026011 (February 2011) Vulnerable plaques constitute a risk for serious heart problems, and are difficult to identify using existing methods. Hyperspectral imaging combines spectral- and spatial information, providing new possibilities for precise optical characterization of atherosclerotic lesions. Hyperspectral data were collected from excised aorta samples (n = 11) using both white-light and ultraviolet illumination. Single lesions (n = 42) were chosen for further investigation, and classified according to histological findings. The corresponding hyperspectral images were characterized using statistical image analysis tools (minimum noise fraction, K-means clustering, principal component analysis) and evaluation of reflectance/fluorescence spectra. Image analysis combined with histology revealed the complexity and heterogeneity of aortic plaques. Plaque features such as lipids and calcifications could be identified from the hyperspectral images. Most of the advanced lesions had a central region surrounded by an outer rim or shoulder-region of the plaque, which is considered a weak spot in vulnerable lesions. These features could be identified in both the white-light and fluorescence data. Hyperspectral imaging was shown to be a promising tool for detection and characterization of advanced atherosclerotic plaques in vitro. Hyperspectral imaging provides more diagnostic information about the heterogeneity of the lesions than conventional single point spectroscopic measurements.
2011
Hyperspectral characterization of fluorophore diffusion in human skin using an sCMOS based hyperspectral camera,

Proc. SPIE-OSA European Conferences on Biomedical Optics 2011, Munich, Germany, May 22-26, 2011

Hyperspectral characterization of fluorophore diffusion in human skin using an sCMOS based hyperspectral camera Julio Ernesto Hernández Palacios, Ingvild Johanne Haug, Øystein Grimstad, Lise Randeberg Proc. SPIE-OSA European Conferences on Biomedical Optics 2011, Munich, Germany, May 22-26, 2011 Hyperspectral fluorescence imaging is a modality combining high spatial and spectral resolution with increased sensitivity for low photon counts. The main objective of the current study was to investigate if this technique is a suitable tool for characterization of diffusion properties in human skin. This was done by imaging fluorescence from Alexa 488 in ex vivo human skin samples using an sCMOS based hyperspectral camera. Pre-treatment with acetone, DMSO and mechanical micro-needling of the stratum corneum created variation in epidermal permeability between the measured samples. Selected samples were also stained using fluorescence labeled biopolymers. The effect of fluorescence enhancers on transdermal diffusion could be documented from the collected data. Acetone was found to have an enhancing effect on the transport, and the results indicate that the biopolymers might have a similar effect. Hyperspectral fluorescence imaging has thus been proven to be an interesting tool for characterization of fluorophore diffusion in ex vivo skin samples. Further work will include repetition of the measurements in a shorter time scale and mathematical modeling of the diffusion process to determine the diffusivity in skin for the compounds in question.
2011
Short communication: Laboratory imaging spectroscopy of soil profiles,

Journal of Spectral Imaging Volume 2 Issue 1, Pages 1–5 (2011).

Short communication: Laboratory imaging spectroscopy of soil profiles Henning Buddenbaum, Markus Steffens Journal of Spectral Imaging Volume 2 Issue 1, Pages 1–5 (2011). An imaging spectrometer in a laboratory rack was used to examine soil profiles. Images in the 400–1000 nm range wih 4nm spectral resolution and less than 0.1mm spatial resolution of the top 30cm of the soil were acquired. These images can be used to analyse the spatial distribution of chemical and physical soil characteristics and for discrimination and classification of horizons and inclusions. Three-dimensional characterisations of soil properties are possible by recording images of series of parallel slices.
2011
Using HySpex SWIR-320m hyperspectral data for the identification and mapping of minerals in hand specimens of carbonate rocks from the Ankloute Formation (Agadir Basin, Western Morocco),

Journal of African Earth Sciences, Volume 61, Issue 1, August 2011, Pages 1-9, ISSN 1464-343X, 10.1016/j.jafrearsci.2011.04.003.

Using HySpex SWIR-320m hyperspectral data for the identification and mapping of minerals in hand specimens of carbonate rocks from the Ankloute Formation (Agadir Basin, Western Morocco) Rachid Baissa, Kamal Labbassi, Patrick Launeau, Anne Gaudin, Brahim Ouajhain Journal of African Earth Sciences, Volume 61, Issue 1, August 2011, Pages 1-9, ISSN 1464-343X, 10.1016/j.jafrearsci.2011.04.003. Nowadays the development of sensors for acquiring hyperspectral images has contributed greatly to the identification of different constituents of the earth’s surface and therefore to the improvement of cartographic products. Carbonate rocks are often altered by physical and chemical processes. The natural tendency in most carbonate sediments is that primary porosity is substantially reduced by cementation and compaction during post-depositional. For example the subaerial meteoric diagenetic (freshwater) was promoted as a means of explaining porosity evolution in carbonates. These processes lead to the formation of new carbonate minerals with highly variable phase crystallization. Frequently, with the optical microscope, the precise identification and discrimination of these phases are beyond the resolving power of the eye, which makes mapping mineralogical microfacies difficult. It requires, first, the use of staining techniques. This work proposes to study hand specimens of the carbonate facies of Jurassic age in the Agadir Basin, using hyperspectral imagery provided by the camera HySpex SWIR-320m, at wavelengths ranging from 1300 to 2500 nm. These images offer the possibility to identify with precision the different carbonate minerals and to allow diagenetic facies characterization. The approach is to calculate an index of carbonate, called the Normalized Difference Carbonate Index or NDCI, to study the deepening of the main absorption band of carbonates and a supervised classification method based on the Spectral Angle Mapper (SAM) to study the overall shape of reflection spectra of carbonates and to map other accessory minerals. This method has allowed the development of mineralogical maps supplemented by their degrees of diagenesis.
2011
SYSIPHE, an airborne hyperspectral imaging system for the VNIR-SWIR-MWIR-LWIR region,

7th EARSeL Workshop on Imaging Spectroscopy, Edinburgh, Scotland, 11th – 13th April, 2011

SYSIPHE, an airborne hyperspectral imaging system for the VNIR-SWIR-MWIR-LWIR region Laurent Rousset-Rouviere, Christophe Coudrain, Sophie Fabre, Ivar Baarstad, Andrei Fridman, Trond Løke, Søren Blaaberg, Torbjørn Skauli 7th EARSeL Workshop on Imaging Spectroscopy, Edinburgh, Scotland, 11th – 13th April, 2011
2011
SYSIPHE - a unique all-band airborne hyperspectral imaging system,

SET-169-RSY-025 NATO SET-169 symposium

SYSIPHE - a unique all-band airborne hyperspectral imaging system Laurent Rousset-Rouviere, Christophe Coudrain, Sophie Fabre, Ivar Baarstad, Andrei Fridman, Trond Løke, Søren Blaaberg, Torbjørn Skauli SET-169-RSY-025 NATO SET-169 symposium
2010
Study of the influence of pre-processing on local statistics-based anomaly detector results,

Whispers 2010, 14 – 16 June 2010, Reykjavik, Iceland

Study of the influence of pre-processing on local statistics-based anomaly detector results Dirk C. Borghys, Christiaan Perneel Whispers 2010, 14 – 16 June 2010, Reykjavik, Iceland Anomaly detection in hyperspectral data has received much attention for various applications and is especially important for defense and security applications. Anomaly detection detects pixels in the hyperspectral data cube whose spectra differ significantly from the background spectra [1]. Most existing methods estimate the spectra of the (local or global) background and then detect anomalies as pixels with a large spectral distance w.r.t. the determined background spectra. Many types of anomaly detectors have been proposed in literature. This paper reports on a sensitivity study that tries to determine an adequate pre-processing chain for anomaly detection in hyperspectral scenes. The study is performed on a set of five hyperspectral datasets and focuses on statisticsbased anomaly detectors.
2010
3D geological modelling using laser and hyperspectral data,

Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International

3D geological modelling using laser and hyperspectral data Juan I. Nieto, Sildomar T. Monteiro, Diego Viejo Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International This paper presents a ground based system for mapping the geology and the geometry of the environment remotely. The main objective of this work is to develop a framework for a mobile robotic platform that can build 3D geological maps. We investigate classification and registration algorithms that can work without any manual intervention. The system capabilities are demonstrated with data acquired from a working mine environment. Geological maps are built by applying classification techniques to hyperspectral images of the rocks' surface. The result from the classification is then fused with laser images to form the 3D geological models of the environment.
2010
Hyperspectral imaging for peach ripening assessment,

7º Colloquium Chemiometricum Mediterraneun (CCM VII 2010 - Granada)

Hyperspectral imaging for peach ripening assessment Lourdes Lleó, Belen Diezma-Iglesias, Jean-Michel Roger, Ana Herrero-Langreo 7º Colloquium Chemiometricum Mediterraneun (CCM VII 2010 - Granada) The present research is focused on the application of artificial vision to peach ripening assessment, avoiding multiplicative and additive effect. Original images were acquired with a hyperspectral camera. Vision allows a spatially detailed determination of the ripening stage of the fruit. Optical indexes are proposed, based on the combination of wavelengths close to the chlorophyll absorption peak at 680 nm. Ind1 corresponds approximately to the depth of the absorption peak, and Ind2 corresponds to the relative absorption peak. An artificial image of each index was obtained by computing the corresponding reflectance images. Score images have been also computed from Principal Components and Partial Least Squares Analysis. In any case the best performances correspond to such images that correct multiplicative and additive effects. Ind2 is the preferred index; it showed the highest discriminating power between ripening stages and no influence of convexity. Ind2 also allowed the differentiation of ripening regions within the fruits, and it showed the evolution of those regions during ripening. This fact has been also observed in some of the score images.
2010
State variables estimationandriparianvegetationspeciesmapping for theNegro river, Spain,by hyperspectral imaging,

Latin American Remote Sensing Week (LARS) 2010 - Chile

State variables estimationandriparianvegetationspeciesmapping for theNegro river, Spain,by hyperspectral imaging Marco Peña, Pablo Cruz, Benjamin Castro Latin American Remote Sensing Week (LARS) 2010 - Chile In  this work we explore  the capacities  that airborne hyperspectral imaging offers  to estimate water's  turbidity  and  depth,  and  to map  riparian  vegetation  species in  the Negro  river,  Spain.  Ground-based data of both state variables, and representative locations of the main tree vegetation species were collected at the same time of the remotely-sensed data acquisition. Correlations were carried out between both data sets in order to find the normalized difference index (NDI) that best relates each state variable. A supervised hyperspectral classifier, trained with field data, was used to map the distribution of the tree species.  Results  show  that  water's  depth  changes  are  best  tracked  by  a  NDI  constructed  with  the  near infrared  (NIR) band at 705.5  nm and a green  visible band at  531.1 nm  (r =  ‐0.69).  Meanwhile, water's  turbidity changes are best tracked by a NDI constructed with the near infrared bands at 905.34 nm, and at 760 or 774.54 nm (r = 0.82). Both results were  found to be consistent with  the  theoretical background.  The  visual  inspection  of  the  output  image  rendered  by  the  classification  algorithm  suggests  that  hyperspectral imaging is encouraging for the riparian vegetation species mapping. An improvement of the methodology employed in this work is expected in the future, in order to provide a solid validation that supports the use of this technology in other water bodies of the country. 
2010
Field hyperspectral imagery as a tool for plant monitoring: application to wheat nitrogen content,

AgEng 2010, Clermont-Ferrand, 6-8 Septembre 2010

Field hyperspectral imagery as a tool for plant monitoring: application to wheat nitrogen content Nathalie Vigneau, Gilles Rabatel, Pierre Roumet, Martin Ecarnot AgEng 2010, Clermont-Ferrand, 6-8 Septembre 2010 In the study presented here, we used a pushbroom CCD camera fitted on a motorised tractor rail to take hyperspectral images of wheat plots. Reflectance correction was performed using a ceramic plate as a reference. The hyperspectral images have been used to build nitrogen (N) content images for wheat plots using two Partial Least Square regression models. The first chemometrical model was calibrated on nitrogen contents (in percentage of dry matter, % DM) obtained in laboratory and flat leaf normalised spectra (5 latent variables, R² = 0.907, RMSEP = 0.326 N % DM); the second one on greenhouse pot plant leaf spectra (8 latent variables, R² = 0.919, RMSEP = 0.412 N % DM). Subsequently, they were directly applied to field plant spectra, providing images of nitrogen content. The range of nitrogen content values in these images was not satisfactory. Due to important spectral differences between greenhouse pot plant leaf spectra and field leaf spectra, a model calibrated directly on field leaves is necessary
2010
Integration of thermal and hyperspectral VNIR imagery for architectural and artistic heritage analysis and monitoring,

Geophysical Research Abstracts, Vol. 12, EGU2010-4919, 2010, EGU General Assembly 2010

Integration of thermal and hyperspectral VNIR imagery for architectural and artistic heritage analysis and monitoring Rosa Maria Cavalli, Nicola Masini, Simone Pascucci, Angelo Palombo, Stefano Pignatti Geophysical Research Abstracts, Vol. 12, EGU2010-4919, 2010, EGU General Assembly 2010 The application of integrated hyperspectral VNIR and thermal data for analyzing and monitoring the architectural and artistic heritage status is becoming a remarkable tool to be combined with other non-destructive techniques (e.g. GPR), and prior to destructive checking, in order to extract appropriate information and make useful decisions
2010
Improved microphytobenthos biomass mapping using hyperspectral images,

Proceedings, Hyperspectral 2010 Workshop’ Frascati, Italy, 17–19 March 2010 (ESA SP-683, May 2010)

Improved microphytobenthos biomass mapping using hyperspectral images Farzaneh Kazemipour, Patrick Launeau, Vona Meleder, Laurent Barillé Proceedings, Hyperspectral 2010 Workshop’ Frascati, Italy, 17–19 March 2010 (ESA SP-683, May 2010) A semi-empirical mapping approach is simplified, improved and applied to ROSIS images to estimate the microphytobenthos (MPB) biomass, expressed in chlorophyll a (mg Chl a.m2). Here we are interested in Diatoms biofilms formed on the sediment surface during the diurnal low tide. The model was applied to large mudflat of Bourgneuf Bay which plays an important economical and environmental role in northwest region of France. Having the hyperspectral images of this study site regularly, such a simple mapping method could be used for a temporal monitoring of region.
2010
Low-light camera for imaging of biological samples,

Proc. IEEE WHISPERS, Reykjavik, Iceland, Jun. 14–16, 2010, pp. 1-4.

Low-light camera for imaging of biological samples Julio Ernesto Hernández Palacios, Ivar Baarstad, Trond Løke, Torbjørn Skauli Proc. IEEE WHISPERS, Reykjavik, Iceland, Jun. 14–16, 2010, pp. 1-4. The capability of acquiring hyperspectral information in low light conditions is potentially important for a variety of applications, ranging from remote sensing to biomedical fluorescence imaging. Particularly interesting is its use in optical analysis of biological samples in which the light level should be kept low to prevent tissue damage. For this purpose a low-light hyperspectral camera has been developed for the 0.4 to 0.9 μm spectral range. The camera is based on an electron-multiplying CCD (EMCCD) detector which effectively suppresses readout noise, and approaches the fundamental photon noise limit. It has been designed with close-up optics to image an area on the order of centimeters. Fluorescence images of skin samples illustrate the camera performance. Results show that low-light hyperspectral imaging has a potential for biomedical applications.
2010
An airborne real-time hyperspectral target detection system,

Proc. SPIE 7695, 76950A (2010), DOI:10.1117/12.850443

An airborne real-time hyperspectral target detection system Torbjørn Skauli, Trym V. Haavardsholm, Ingebjørg Kåsen, Gunnar Arisholm, Amela Kavara, Atle Skaugen Proc. SPIE 7695, 76950A (2010), DOI:10.1117/12.850443
2010
A New Approach to Microphytobenthos Biomass Mapping by Inversion of the Radiative Transfer Model: Application to Hyspex Images of Bourgneuf Bay,

IGARSS 2010, July 25-30, Hawaii

A New Approach to Microphytobenthos Biomass Mapping by Inversion of the Radiative Transfer Model: Application to Hyspex Images of Bourgneuf Bay Farzaneh Kazemipour, Patrick Launeau, Vona Meleder IGARSS 2010, July 25-30, Hawaii
2010
Clustering of Crop Phenotypes by Means of Hyperspectral Signatures Using Artificial Neural Networks,

Whispers 2010, 14 – 16 June 2010, Reykjavik, Iceland

Clustering of Crop Phenotypes by Means of Hyperspectral Signatures Using Artificial Neural Networks Udo Seiffert, Felix Bollenbeck, Hans-Peter Mock, Andrea Matros Whispers 2010, 14 – 16 June 2010, Reykjavik, Iceland Hyperspectral imaging linked to subsequent neural networks based analysis has proven its suitability to unravel complex information in a number of different application areas, such as geology, defence, etc. The extension of this approach to crop plant research, plant breeding, and agriculture has started quite recently. Here, the image acquisition ranges from airborne sensing mainly for agricultural applications down to single leaf analysis in the context of precision and high-throughput plant phenotyping. All these applications have in common, that particular relevant compounds of the plant need to be determined by means of hyperspectral signatures as substitute to extensive biochemical analysis. This paper describes the quantitative assessment of a number of genetically different tobacco varieties (Nicotiana tabacum) that were grown under different environmental and nutritional conditions. The analysis of the measured hyperspectral signatures was done by artificial neural networks.
2010
Characterisation of vascular structures and skin bruises using hyperspectral imaging, image analysis and diffusion theory,

J.Biophoton. 3, No. 1-2, 53-65 (2010)

Characterisation of vascular structures and skin bruises using hyperspectral imaging, image analysis and diffusion theory Lise Randeberg, Eivind Larsen, Lars Svaasand J.Biophoton. 3, No. 1-2, 53-65 (2010)
2009
Close range hyperspectral and lidar data integration for geological outcrop analysis,

Proceedings of First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing

Close range hyperspectral and lidar data integration for geological outcrop analysis Tobias H. Kurz, Simon J. Buckley, John A. Howell Proceedings of First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing The use of spatial data collection techniques in geology has increased significantly in recent years, with methods such as laser scanning (lidar) becoming popular. However, the remote mapping of rock properties within the geological outcrops remains a major challenge. This study develops a workflow for combining and utilising ground based hyperspectral and laser scanning data. This workflow is presented for two case studies, each with different geological settings and mineral composition. Multiple hyperspectral and lidar scans were acquired to gain both spectral and geometric data. Mixture Tuned Matched Filtering was utilised to extract and map geological features from the spectral images, resulting in thematic images. This combination of geometrically accurate lidar data and spectral mapping of lithology has significant implications for the improved collection of geological data.
2009
Deteksjon av eksplosivrester i felt ved hjelp av hyperspektral avbildning,

FFI-rapport 2009/01426

Deteksjon av eksplosivrester i felt ved hjelp av hyperspektral avbildning Leif Amund Lie, Torbjørn Skauli, Tove Engen Karsrud, Marthe Petrine Parmer FFI-rapport 2009/01426 Military firing ranges are known to be contaminated by particles of explosives, mainly due to incomplete detonations of munitions. The explosive particles are difficult to find, but are considered to pose an environmental hazard because the substances are poisonous, to a varying degree. Hyperspectral imaging is a technology which exploits the information contained in the spectrum of light, to map the distribution of different materials. This report describes preliminary experiments with detection of explosives using hyperspectral imaging. The results indicate that explosives exhibit spectral signatures that can be exploited for detection. The report forms the basis for an initial assessment of the utility of hyperspectral imaging to identify hot spots of explosives.
2009
IDC-improved direct calibration: a new direct calibration method applied to hyperspectral image analysis,

First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing

IDC-improved direct calibration: a new direct calibration method applied to hyperspectral image analysis Jean-Claude Boulet, Nathalie Gorretta-Monteiro, Jean-Michel Roger First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing
2009
Summary of capacities and potential applications of the first chilean hyperspectral system,

Proceedings of the 24th International Cartographic Conference: The World’s GeoSpatial Solutions. 15– 21 November 2009. Military School: Santiago, Chile.

Summary of capacities and potential applications of the first chilean hyperspectral system Marco Peña Proceedings of the 24th International Cartographic Conference: The World’s GeoSpatial Solutions. 15– 21 November 2009. Military School: Santiago, Chile. Remote sensing is a scientific discipline that retrieves physical and chemical information of an element by detecting and analyzing its radiated energy at given spectral wavelength intervals. During the 80’s decade advances in spectroscopy imagery allowed for the creation of the first airborne hyperspectral imaging spectroradiometers. Since then, they have gained increased reputation for Earth’s natural resource surveys, mostly in developed countries. Currently, this technology is being implemented in Chile also, through the Prototype System of Hyperspectral Remote Sensing (Sistema Prototipo de Observación Remota Hiperespectral, SPORH). SPORH is the first Chilean initiative that offers to any interested user imagery, thematic cartography and information of the national agricultural and forest lands derived from our own hyperspectral scanner. The system has been originally designed to operate at local spatial scales in order to provide relatively economical “just in time” products to small owners (e.g., winegrowers). Nevertheless, applications at larger spatial scales will also be considered.
2009
Snapshot active polarimetric and multispectral laboratory demonstrator,

Laser Radar Technology and Applications XIV, edited by Monte D. Turner, Gary W. Kamerman, Proc. of SPIE Vol. 7323, 732310 · 2009 SPIE · CCC code: 0277-786X/09/$18 · doi: 10.1117/12.820052

Snapshot active polarimetric and multispectral laboratory demonstrator Arnaud Bénière, Mehdi Alouini, François Goudail, Arnaud Grisard, Jérôme Bourderionnet, Daniel Dolfi, Ivar Baarstad, Trond Løke, Peter Kaspersen, Xavier Normandin, Gerard Berginc Laser Radar Technology and Applications XIV, edited by Monte D. Turner, Gary W. Kamerman, Proc. of SPIE Vol. 7323, 732310 · 2009 SPIE · CCC code: 0277-786X/09/$18 · doi: 10.1117/12.820052 In this article we address the design and exploitation of a real field laboratory demonstrator combining active polarimetric and multispectral modes in a single acquisition. Its buildings blocks, including a multi-wavelength pulsed optical parametric oscillator at emission side, and a hyperspectral imager with polarimetric capability at reception side, are described. The results obtained with this demonstrator are illustrated on some examples and discussed.
2009
Hyperspectral imaging of blood perfusion and chromophore distribution in skin,

Photonic Therapeutics and Diagnostics V, Proc. of SPIE Vol. 7161, 71610C · © 2009 SPIE · CCC code: 1605-7422/09/$18 · doi: 10.1117/12.810027

Hyperspectral imaging of blood perfusion and chromophore distribution in skin Lise Randeberg, Eivind Larsen, Lars Svaasand Photonic Therapeutics and Diagnostics V, Proc. of SPIE Vol. 7161, 71610C · © 2009 SPIE · CCC code: 1605-7422/09/$18 · doi: 10.1117/12.810027 Hyperspectral imaging is a modality which combines spatial resolution and spectroscopy in one technique. Analysis of hyperspectral data from biological samples is a demanding task due to the large amount of data, and due to the complex optical properties of biological tissue. In this study it was investigated if depth information could be revealed from hyperspectral images using a combination of image analysis and analytic simulations of skin reflectance. It was also investigated if hyperspectral imaging could be utilized to monitor changes in the distribution of hemoglobin species after smoking. Hyperspectral data in the wavelength range 400-1000nm were collected from the forearm of 15 non-smokers and 5 smokers. The hyperspectral images were analyzed with respect to the distribution of hemoglobin species and vascular structures. Changes in the vascular system due to smoking were also evaluated. Principal component analysis (PCA), Spectral angle mapping (SAM), and Mixture tuned matched filtering (M
2009
Cartographie des Estrans Rocheux de Normandie par Télédétection Hyperspectrale,

CHARAMB'AR, 04.02.2009

Cartographie des Estrans Rocheux de Normandie par Télédétection Hyperspectrale Pascal Mouquet, Loïc Lozach, Patrick Dion, Éric de Oliveira, Franck Bruchon, Marc Lennon CHARAMB'AR, 04.02.2009 Algue
2009
Characterization of vascular structures and skin bruises using hyperspectral imaging, image analysis and diffusion theory,

Journal of Biophotonics, September 8th 2009.

Characterization of vascular structures and skin bruises using hyperspectral imaging, image analysis and diffusion theory Lise Randeberg, Eivind Larsen, Lars Svaasand Journal of Biophotonics, September 8th 2009.
2009
Design and characterization of a hyperspectral camera for low light imaging with example results from field and laboratory applications,

6th EARSeL, Tel Aviv, Israel, March 16-18, 2009.

Design and characterization of a hyperspectral camera for low light imaging with example results from field and laboratory applications Julio Ernesto Hernández Palacios, Ivar Baarstad, Trond Løke, Lise Randeberg, Torbjørn Skauli 6th EARSeL, Tel Aviv, Israel, March 16-18, 2009.
2009
Proposition d’une approche de segmentation d’images hyperspectrale,

Doctoral thesis, 1st of March 2009, Universite Montpellier.

Proposition d’une approche de segmentation d’images hyperspectrale Nathalie Gorretta-Monteiro Doctoral thesis, 1st of March 2009, Universite Montpellier.
2009
Application of TLS for Change Detection in Rock Faces,

ISPRS Workshop, Laserscanning ‘09, September, 2009

Application of TLS for Change Detection in Rock Faces Mario Alba, Fabio Roncoroni, Marco Scaioni ISPRS Workshop, Laserscanning ‘09, September, 2009
2009
Anomaly detection in hyperspectral images of complex scenes,

29th EARSeL Symposium, MAI Chania, 15 – 18 June 2009.

Anomaly detection in hyperspectral images of complex scenes Dirk C. Borghys, Michal Shimoni, Christiaan Perneel 29th EARSeL Symposium, MAI Chania, 15 – 18 June 2009. The aim of anomaly detection in hyperspectral image processing is to detect pixels in the hyperspectral datacube that exhibit spectral signatures that are exceptional in the investigated scene. The current paper investigates the detection of anomalies in complex environments, i.e. urban and industrial scenes. The classical anomaly detection consists of a local measurement of differences between the spectral signature of the pixel and the average spectral signature of its surroundings. In complex environments such an approach is not adequate because of the high spatial variation of the background spectral features. Approaches based on global image segmentation have already been proposed in literature. This paper proposes a two-level segmentation based approach. In the first step of the method a scanning window is moved over the image. At each position a few characteristic spectra are determined. This is done either by spectral clustering or end-member selection methods. Then the image tile, defined by the curent position of the scanning window, is classified using the determined spectra and only the spectra to which at least a given percentage of the image tile’s pixels is assigned, are stored. At the end of the process the most characteristic spectra are searched within the collected set of spectra. This is again done by clustering or endmember selection. The final anomaly detection result is determined using a distance classifier or by spectral unmixing, based on the selected characteristic spectra. The method is tested and evaluated on three hyperspectral scenes with diverse complexity and acquired by three different airborne sensors. For evaluation purposes, the proposed methods are compared to two existing global image segmentation approaches and to the local Reed Xiaoli (RX) detector.
2009
Hyperspectral image segmentation: The butterfly approach,

First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2009. WHISPERS, 26-28 Aug. 2009 Page(s):1 – 4.

Hyperspectral image segmentation: The butterfly approach Nathalie Gorretta-Monteiro, Jean-Michel Roger, Gilles Rabatel, Véronique Bellon- Maurel, Christophe Fiorio, Camille Lelong First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2009. WHISPERS, 26-28 Aug. 2009 Page(s):1 – 4. Few methods are proposed in the litterature for coupling the spectral and the spatial dimension available on hyperspectral images. This paper proposes a generic segmentation scheme named butterfly based on an iterative process and a cross analysis of spectral and spatial information. Indeed, spatial and spatial structures are extracted in spatial and spectral space respectively both taking into account the other one. To apply this layout on hyperspectral imgages, we focus particulary on spatial and spectral structures i.e. topologic concepts and latent variable for the spatial and the spectral space respectively. Moreover, a cooperation scheme with these structures is proposed. Finally, results obtained on real hyperspectral images using this specific implementation of the butterfly approach are presented and discussed.
2009
Hyperspectral characterization of microphytobenthic biofilms,

Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2009. WHISPERS apos;09. First Workshop on Volume , Issue , 26-28 Aug. 2009 Page(s):1 - 4.

Hyperspectral characterization of microphytobenthic biofilms Farzaneh Kazemipour, Patrick Launeau, Vona Meleder Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2009. WHISPERS apos;09. First Workshop on Volume , Issue , 26-28 Aug. 2009 Page(s):1 - 4.
2008
Application of image processing techniques for enhancement and segmentation of bruises in hyperspectral images,

ASLMS 28th Annual Meeting, Kissimmee, Florida, (2008).

Application of image processing techniques for enhancement and segmentation of bruises in hyperspectral images Lise Randeberg, Henrik Mogens Gundersen, Bjørn F. Rasmussen, Lars Svaasand ASLMS 28th Annual Meeting, Kissimmee, Florida, (2008).
2008
Hyperspectral imaging of the porcine heart,

Norwegian Electro-Optics Meeting, Tromsø, Norway (2008).

Hyperspectral imaging of the porcine heart Eivind Larsen, Lise Randeberg, Astrid Aksnes Norwegian Electro-Optics Meeting, Tromsø, Norway (2008).
2008
Application of image processing techniques for enhancement and segmentation of vascular structures and bruises in hyperspectral images,

NOBIM 2008, Trondheim, Norway, (2008).

Application of image processing techniques for enhancement and segmentation of vascular structures and bruises in hyperspectral images Lise Randeberg, Henrik Mogens Gundersen, Bjørn F. Rasmussen, Jørgen Bru, Lars Svaasand NOBIM 2008, Trondheim, Norway, (2008).
2008
Tissue characterization and optical diagnostics by diffuse reflectance spectroscopy and hyperspectral imaging,

Seminar at the Department of Solid State Physics, Jožef Stefan Institute, Ljubljana, Slovenia, (June 2008).

Tissue characterization and optical diagnostics by diffuse reflectance spectroscopy and hyperspectral imaging Lise Randeberg Seminar at the Department of Solid State Physics, Jožef Stefan Institute, Ljubljana, Slovenia, (June 2008).
2008
Some practical issues in anomaly detection and exploitation of regions of interest in hyperspectral images,

Applied Optics (2008).

Some practical issues in anomaly detection and exploitation of regions of interest in hyperspectral images François Goudail, Nicolas Roux, Ivar Baarstad, Trond Løke, Peter Kaspersen, Mehdi Alouini Applied Optics (2008).
2008
Near infrared active polarimetric and multispectral laboratory demonstrator for target detection,

Applied Optics (2008).

Near infrared active polarimetric and multispectral laboratory demonstrator for target detection Mehdi Alouini, François Goudail, Arnaud Grisard, Jérôme Bourderionnet, Daniel Dolfi, Arnaud Bénière, Ivar Baarstad, Trond Løke, Peter Kaspersen, Xavier Normandin, Gerard Berginc Applied Optics (2008).
2008
Band selection for hyperspectral target detection based on a multinormal mixture anomaly detection algorithm,

Algorithms and Tecnologies for Multispectral, Hyperspectral and Ultraspectral Imagery XIV, Proc. Of the SPIE, Volume 6966, (2008).

Band selection for hyperspectral target detection based on a multinormal mixture anomaly detection algorithm Ingebjørg Kåsen, Anders Rødningsby, Trym V. Haavardsholm, Torbjørn Skauli Algorithms and Tecnologies for Multispectral, Hyperspectral and Ultraspectral Imagery XIV, Proc. Of the SPIE, Volume 6966, (2008).
2008
Fish freshness assessment as part of an automatic fillet inspection,

presented at WEFTA 2008, Florence, Italy (2008).

Fish freshness assessment as part of an automatic fillet inspection Karsten Heia, Agnar Holten Sivertsen presented at WEFTA 2008, Florence, Italy (2008).
2008
Automatic cod fillet inspection by imaging spectroscopy,

presented at WEFTA 2008, Florence, Italy (2008).

Automatic cod fillet inspection by imaging spectroscopy Karsten Heia, Agnar Holten Sivertsen presented at WEFTA 2008, Florence, Italy (2008).
2008
Ridge detection with application to automatic fish fillet inspection,

Journal of Food Engineering (2008).

Ridge detection with application to automatic fish fillet inspection Agnar Holten Sivertsen, Chih-Kang Chu, Lih-Chung Wang, Fred Godtliebsen, Karsten Heia, Heidi Nilsen Journal of Food Engineering (2008).
2008
Geological outcrop modelling and interpretation using ground based hyperspectral and laser scanning data fusion,

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B8. Beijing (2008).

Geological outcrop modelling and interpretation using ground based hyperspectral and laser scanning data fusion Tobias H. Kurz, Simon J. Buckley, John A. Howell, Danilo Schneider The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B8. Beijing (2008).
2008
Evaluation of the Atmospheric Correction Procedure for the APEX Level 2/3 Processor,

presented at SPIE Remote Sensing Europe, Cardiff, UK (2008).

Evaluation of the Atmospheric Correction Procedure for the APEX Level 2/3 Processor Daniel Schläpfer, Jan Biesemans, Andreas Hueni, Koen Meuleman presented at SPIE Remote Sensing Europe, Cardiff, UK (2008).
2008
Detection of parasites in fish – developing an industrial solution,

Infofish International, 3/2008.

Detection of parasites in fish – developing an industrial solution Agnar Holten Sivertsen, Karsten Heia, Heidi Nilsen Infofish International, 3/2008.
2008
A 4d morphological scale space representation for hyperspectral imagery,

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing 2008.

A 4d morphological scale space representation for hyperspectral imagery Konstantinos Karantzalos The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing 2008. In this paper, a 4D scale space representation is introduced aiming at denoising, smoothing and simplifying effectively airborne and spaceborne hyperspectral imagery. Our approach is based on a novel morphological levelings’ vectorial formulation, which by integrating spatial and spectral information is able to produce elegantly simpli?ed versions (scale spaces) of the initial hypercube. In addition, their construction is constrained by vector-valued anisotropic diffused markers which still respect the special hyperspectral data properties. In contrast to earlier efforts, under such a morphological framework the simpli?ed scale space hypercubes are not characterized by spurious extrema or asymmetrical intensity shifts and their edges/contours are not displaced. Experimental results demonstrate the potential of our approach, indicating that the proposed representation outperforms earlier ones in quantitative and qualitative evaluation.
2008
Leaf area index estimation using lidar and forest reflectance modelling of airborne hyperspectral data,

IGARSS 2008.

Leaf area index estimation using lidar and forest reflectance modelling of airborne hyperspectral data Holger Lange, Svein Solberg IGARSS 2008.
2008
Status of the Norwegian hyperspectral technology demonstrator,

In Proc. of NATO SET-130 ”NATO Military sensing symposium", Orlando, Florida, USA, 2008, pp. F5–1–F5–6.

Status of the Norwegian hyperspectral technology demonstrator Torbjørn Skauli, Ingebjørg Kåsen, Trym V. Haavardsholm, Amela Kavara, Yuliya Tarabalka, Øystein Farsund In Proc. of NATO SET-130 ”NATO Military sensing symposium", Orlando, Florida, USA, 2008, pp. F5–1–F5–6.
2008
Geological Outcrop Modelling and Interpretation Using Ground Based Hyperspectral and Laser Scanning Data Fusion,

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences,37(B8): 1229-1234. 2008.

Geological Outcrop Modelling and Interpretation Using Ground Based Hyperspectral and Laser Scanning Data Fusion Tobias H. Kurz, Simon J. Buckley, John A. Howell, Danilo Schneider International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences,37(B8): 1229-1234. 2008.
2008
Real-time anomaly detection in hyperspectral images using multivariate normal mixture models and GPU processing,

Journal of Real-Time Image Processing, ISSN 1861-8200, (2008).

Real-time anomaly detection in hyperspectral images using multivariate normal mixture models and GPU processing Yuliya Tarabalka, Trym V. Haavardsholm, Ingebjørg Kåsen, Torbjørn Skauli Journal of Real-Time Image Processing, ISSN 1861-8200, (2008).
2007
A New Method to Retrieve the Data Requirements of the Remote Sensing Community – Exemplarily Demonstrated for Hyperspectral User Needs,

Sensors 2007, 7, 1545-1558. (ISSN 1424- 8220).

A New Method to Retrieve the Data Requirements of the Remote Sensing Community – Exemplarily Demonstrated for Hyperspectral User Needs Jens Nieke, Ils Reusen Sensors 2007, 7, 1545-1558. (ISSN 1424- 8220).
2007
Evaluation of user-oriented attractiveness of imaging spectroscopy data using the value-benefitanalysis (VBA),

5th EARSeL Workshop on Imaging Spectroscopy, Belgium, April 23-25 2007.

Evaluation of user-oriented attractiveness of imaging spectroscopy data using the value-benefitanalysis (VBA) Jens Nieke, Bruno Seiler, Klaus I. Itten, Ils Reusen, Stefan Adriaensen 5th EARSeL Workshop on Imaging Spectroscopy, Belgium, April 23-25 2007.
2007
Classification of crops using an airborne hyper-spectral imager,

Poster paper of the 6th European Conference on Precision Agriculture (ECPA), June 3-6, Skiathos, Greece, p. 1-6 (on CD), (2007).

Classification of crops using an airborne hyper-spectral imager Audun Korsæth, Hans Ole Ørka Poster paper of the 6th European Conference on Precision Agriculture (ECPA), June 3-6, Skiathos, Greece, p. 1-6 (on CD), (2007).
2007
In vivo hyperspectral imaging of fresh, non-penerating traumatic skin injuries,

Annual meeting, Norwegian Society for Photobiology and Photomedicine 2006, Oslo, Norway (2007).

In vivo hyperspectral imaging of fresh, non-penerating traumatic skin injuries Lise Randeberg, Andreas M. Winnem, Eivind Larsen, Rune Haaverstad, Olav A. Haugen, Lars Svaasand Annual meeting, Norwegian Society for Photobiology and Photomedicine 2006, Oslo, Norway (2007).
2007
Effect of light level and photon noise on hyperspectral target detection performance,

Proceedings of SPIE, vol. 6661 (2007).

Effect of light level and photon noise on hyperspectral target detection performance Torbjørn Skauli, Rikke Ingebrigtsen, Ingebjørg Kåsen Proceedings of SPIE, vol. 6661 (2007).
2007
A Scene Based Method For Spatial Misregistration Detection In Hyperspectral Imagery,

Applied Optics 2007.

A Scene Based Method For Spatial Misregistration Detection In Hyperspectral Imagery Dell'Endice Francesco, Jens Nieke, Daniel Schläpfer, Klaus I. Itten Applied Optics 2007.
2007
Detection of nematodes in Cod (Gadus morhua) fillets by imaging spectroscopy,

Journal of Food Science, (2007).

Detection of nematodes in Cod (Gadus morhua) fillets by imaging spectroscopy Karsten Heia, Agnar Holten Sivertsen, Svein K. Stormo, Edel Elvevoll, Jens Petter Wold, Heidi Nilsen Journal of Food Science, (2007).
2007
A physics-based statistical signature model for hyperspectral target detection,

Geoscience and Remote Sensing Symposium, IGARSS 2007.

A physics-based statistical signature model for hyperspectral target detection Trym V. Haavardsholm, Torbjørn Skauli, Ingebjørg Kåsen Geoscience and Remote Sensing Symposium, IGARSS 2007.
2007
Forest reflectance modelling of hyperspectral data,

ForestSat 2007, Montpellier, France (2007).

Forest reflectance modelling of hyperspectral data Svein Solberg, Holger Lange ForestSat 2007, Montpellier, France (2007).
2007
Testing remote sensing techniques for monitoring large scale insect defoliation,

ForestSat 2007, Montpellier, France (2007).

Testing remote sensing techniques for monitoring large scale insect defoliation Svein Solberg, Lars Eklundh, Arnt Kristian Gjertsen, Tomas Johansson, Steve Joyce, Holger Lange, Erik Næsset, Håkan Olsson, Yong Pang, Anne Solberg ForestSat 2007, Montpellier, France (2007).
2007
Mapping trees and thicket with optical images,

Hedmark University College, Oppdragsrapport nr. 5-2007, 36 pages (2007).

Mapping trees and thicket with optical images Floris Jan Groesz, Leif Kastdalen Hedmark University College, Oppdragsrapport nr. 5-2007, 36 pages (2007).
2007
In vivo hyperspectral imaging of traumatic skin injuries in a porcine model,

Proceedings of SPIE, Vol. 6424, 2007.

In vivo hyperspectral imaging of traumatic skin injuries in a porcine model Lise Randeberg, Andreas M. Winnem, Eivind Larsen, Rune Haaverstad, Olav A. Haugen, Lars Svaasand Proceedings of SPIE, Vol. 6424, 2007.
2006
Superresolution of hyperspectral images,

Chemometrics and intelligent laboratory systems 2006, vol. 84, no1-2, pp. 62-68.

Superresolution of hyperspectral images Bård Buttingsrud, Bjørn K. Alsberg Chemometrics and intelligent laboratory systems 2006, vol. 84, no1-2, pp. 62-68.
2006
Hyperspectral and multispectral perspectives on the prehistoric cultural landscape; the ground-truthed chemical character of prehistoric settlement and infrastructure as identified from space,

Proceedings of the 2nd International Workshop, CNR, Rome, Italy, December 4-7, 2006, Archeopress, BAR S1568, Oxford (2006).

Hyperspectral and multispectral perspectives on the prehistoric cultural landscape; the ground-truthed chemical character of prehistoric settlement and infrastructure as identified from space Ole Grøn, Finn Christensen, Pietro Orlando, Ivar Baarstad, Richard Macphail Proceedings of the 2nd International Workshop, CNR, Rome, Italy, December 4-7, 2006, Archeopress, BAR S1568, Oxford (2006).
2006
A compact combined hyperspectral and polarimetric imager,

Proceedings of SPIE vol. 6395 (2006).

A compact combined hyperspectral and polarimetric imager Torbjørn Skauli, Pål Erik Goa, Ivar Baarstad, Trond Løke Proceedings of SPIE vol. 6395 (2006).
2006
Hyperspectral imaging of bruised skin,

Proceedings of SPIE vol. 6078 (2006).

Hyperspectral imaging of bruised skin Lise Randeberg, Ivar Baarstad, Trond Løke, Peter Kaspersen, Lars Svaasand Proceedings of SPIE vol. 6078 (2006).
2006
Yield estimates from remotely sensed information,

NJF-seminar no. 390, November 7-8, Lillehammer, Norway. Published in: NJF Report 2(8) 2006: 91-93 (2006).

Yield estimates from remotely sensed information Audun Korsæth, Hans Ole Ørka NJF-seminar no. 390, November 7-8, Lillehammer, Norway. Published in: NJF Report 2(8) 2006: 91-93 (2006).
2005
Monitoring forest health by remote sensing of canopy chlorophyll: first results from a pilot project in Norway,

Proc. 31st International Symposium on Remote Sensing of Environment. Global monitoring for sustainability and security. June 20 - 24, 2005, Saint Petersburg, Russian Federation. CD-ROM.

Monitoring forest health by remote sensing of canopy chlorophyll: first results from a pilot project in Norway Svein Solberg, Holger Lange, Lars Aurdal, Rune Solberg, Erik Næsset Proc. 31st International Symposium on Remote Sensing of Environment. Global monitoring for sustainability and security. June 20 - 24, 2005, Saint Petersburg, Russian Federation. CD-ROM.
2005
Remote sensing of foliar mass and chlorophyll as indicators of forest health: preliminary results from a project in Norway,

In: Olsson, H. (Ed.) Proceedings of ForestSat 2005, Borås, May 31-June 3. Rapport 8a.

Remote sensing of foliar mass and chlorophyll as indicators of forest health: preliminary results from a project in Norway Svein Solberg, Erik Næsset, Lars Aurdal, Holger Lange, Ole Martin Bollandsås, Rune Solberg In: Olsson, H. (Ed.) Proceedings of ForestSat 2005, Borås, May 31-June 3. Rapport 8a.
2005
The effect of spatial resolution on hyperspectral target detection performance,

Proceedings of SPIE, vol. 5987 (2005).

The effect of spatial resolution on hyperspectral target detection performance Torbjørn Skauli, Ingebjørg Kåsen Proceedings of SPIE, vol. 5987 (2005).
2005
ASI, A new airborne hyperspectral imager,

Proceedings of 4th EARSeL Workshop on Imaging Spectroscopy, Warsaw, Poland (2005).

ASI, A new airborne hyperspectral imager Ivar Baarstad, Trond Løke, Peter Kaspersen Proceedings of 4th EARSeL Workshop on Imaging Spectroscopy, Warsaw, Poland (2005).
2004
Physical subspace models for invariant material identification: subspace dimensionality and detection performance,

Proceedings of SPIE, vol. 5573 (2004).

Physical subspace models for invariant material identification: subspace dimensionality and detection performance Pål Erik Goa, Torbjørn Skauli, Ingebjørg Kåsen, Trym V. Haavardsholm, Anders Rødningsby Proceedings of SPIE, vol. 5573 (2004).
2004
Target detection in hyperspectral images based on multi-component statistical models for representation of background clutter,

Proceedings of SPIE, vol. 5612 (2004).

Target detection in hyperspectral images based on multi-component statistical models for representation of background clutter Ingebjørg Kåsen, Pål Erik Goa, Torbjørn Skauli Proceedings of SPIE, vol. 5612 (2004).
2004
Remote sensing of forest health,

Proc. of SNS meeting in forest pathology, Norway, September 2005. Pp 161-166 in: Thies, M., Koch, B., Spiecker, H. & Weinacker, H. (eds.). Laser-Scanners for Forest and Landscape Assessment. - Natscan International Conference on Laser Scanners for Forest and Landscape Assessment, Freiburg 2004. ISPRS Archives 36.

Remote sensing of forest health Svein Solberg Proc. of SNS meeting in forest pathology, Norway, September 2005. Pp 161-166 in: Thies, M., Koch, B., Spiecker, H. & Weinacker, H. (eds.). Laser-Scanners for Forest and Landscape Assessment. - Natscan International Conference on Laser Scanners for Forest and Landscape Assessment, Freiburg 2004. ISPRS Archives 36.