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Hyperspectral Imaging

Members

Activities

The hyperspectral group investigates the use of hyperspectral data and the combined use of hyperspectral data with other types of data for Security and Defense applications. Topics of interest include target, anomaly and change detection, land-use and land-cover classification, spectroscopy in the very near and thermal infra-red domains, the unmixing of spectral curves and the fusion of hyperspectral data with other state-of-the-art sensors, such as LIDAR, optical and thermal images. A correct interpretation of hyperspectral data involves the application of atmospheric corrections, the detection and suppression of shadows, extensive physics based modelling and temperature-emissivity separation of the thermal hyperspectral data. The applications of interest cover the urban environment, industrial infrastructure and security, detection of gasses and pollution, maritime environment and leads to an assessment of security and risks.

Image processing and analysis algorithms are applied and developed for each of application domain. The acquired information allows the group to advice new uses and requirements of airborne and spaceborne hyperspectral data within Defense.

A continuous effort is made for collecting new data, either from different sensors or for different applications. Sensor and sensor-platform development and evolution is also followed in order to be aware of the implications of new developments on solving various security and defense related problems.

Research projects

Modelling and forecasting African Urban Population Patterns for vulnerability and health assessments - MAUPP

Description:

MAUPP aims to improve our spatial understanding, prediction and forecast of urbanization and urban population in Africa through the use of remote sensing and spatial modelling. The project addresses two specific objectives:

- Produce an urban expansion model at moderate spatial resolution for African cities. This objective will be achieved through i) using HRRS and VHRRS (both optical and radar) to delineate urban extent of a set of cities, compare the accuracy and limitations of the obtained features and optimize the method based on HRRS, ii) using of the best methods identified using HRRS to generate a database of land cover change to urban over the last 30 years across a large number of cities in Africa, iii) using this database to build urban expansion models, evaluate their forecasting accuracy, and apply them to forecast the future distribution of the major urban extents in Africa.

- Understand and predict intra-urban variations in human population density in Afr

GEotechnical and Patrimonial Archives Toolbox for ARchitectural conservation in Belgium (GEPATAR)

GEPATAR focuses on the collection of data necessary for future preservation activities. For the majority of Belgian people, the country geologically speaking is more or less safe: no volcano, no major earthquake, and no major landslide. However, neo-ground movements are occurring and they are originated from industrial exploitation of the subsoil, urbanization and (des) industrialization processes, and may also be induced by several local phenomena. Ground movements may significantly affect the buildings and contribute to degradation of their structural stability. GEPATAR will develop tools to explore two large federal archive facilities: the RBINS satellite archive and the KIK-IRPA patrimony heritage data base. Dedicated permanent scattering tool will allow the efficient exploitation of hundreds satellite SAR archive data for ground movement mapping with millimeters accuracy. This risk map will permit a geographical search for selected heritage buildings that might be in risk at the K

C4/23

The general objective of this study is to investigate the potential benefit of fused high spatial and spectral resolution imagery and 3D airborne data for several defence applications in urban and harbour areas. The study will evaluate the improvement of the situation awareness and surveillance capability in complex urban and harbour areas using the addressed STARs.

RESPOND-ISVG

This project PROVIDES an external expertise to ?Respond? project of the GMES framework.

Respond is an alliance of European and International organisations working with the humanitarian community to improve access to maps, satellite imagery and geographic information.

The role of the RMA in the project is to give an expertise in:

-The validation of the RESPONDS?s map products and mainly flood maps;

-To assess the map validation process,

-To propose improvements.

Airborne sensor system for the protection of the marine environment (ASME)

This project to be funded by the "federal public service for health, food chain safety and environment", concerns a feasibility analysis on the use of sensors like synthetic aperture radar, thermal infrared camera or scanners and hyperspectral imaging spectrometers to enhance the protection of the marine environment (detection in time of pollutions).

This work will be performed in four constructive parts. In the first part, the UGMM operational needs will be gathered and analysed. In the second part, sensors or a set of sensors required to fulfil the end-user’s operational needs will be listed and for each sensor the spectral, spatial, radiometrical and temporal requirements will be derived. In the third part, the necessary adaptations will be listed that should be made to the available airborne platform. And in the fourth part, a costs analysis for off-the-shelf sensor/s acquisition, adapted hardware and adaptation to the airborne platform will be produced.

polinsar (2006)

In the framework of this project, the RMA is in charge of performing fusion of PolInSAR data at different levels (low, intermediate and high) and to evaluate, with the other partners and potential users, the potential of PolInSAR in remote sensing.

TIRIS - “Measuring chemical pollutant gases in the port of Antwerp using imaging spectroscopy”

The objective of this project is to detect presence and concentration of polluted gas compounds in the atmosphere using airborne MWIR and LWIR imaging spectroscopy data. AHS-160 data have been collected over a chemical industry situated in the port of Antwerp, during two operational periods on the same day. The airborne data have been calibrated and verified using numerous ground truth measurements collected using field thermal imaging reflectometer (SOC 400T) and traditional in-situ measurements collected in air quality monitoring stations in the port. The image processing uses non-linear absorption features of target gases spectral signature coupled with background suppression techniques to obtain absolute plume column density and plume temperature.

HYTIR “Feasibility Study on Hyperspectral Thermal Infrared Sensor”

This projects consists in the realisation of a feasibility study to set up requirement consolidation for future hyperspectral thermal infrared imager space mission devoted to dual “civil” and “security” applications.

<p>The feasibility study will provide a review of potential applications of hyperspectral TIR instruments, derivation of instrument requirements and state-of-the-art survey of spaceborne and airborne TIR hyperspectral relevant instrumentation.</p>

Advanced Space Techn to support Sec Ops

This project aims to show to EU stakeholders the potential of using Space to support Security operations. The objectives being to demonstrate to the users its unique advantages in specific situations: non intrusive and legal, available everywhere at any time, robust and non-vulnerable to local threats; and to propose a structured and effective access to the EU resources providing timely response in security-related situations.

HYSAR

This research aims at performing data fusion between polarimetric and interferometric SAR data on the one hand and hyperspectral data on the other hand in order to classify man-made object in urban and industrial scenes.

Publications

  1. J-F Lopez, M Shimoni, and T Grippa. Extraction of African urban and rural structural features using SAR sentinel-1 data. In IEEE Joint Urban Remote Sensing Event (JURSE), Dubai, 2017.
  2. M Shimoni, J Lopez, J Walstra, P y Declercq, L Bejarano-Urrego, E Verstrynge, D Derauw, R Hayen, and K Van Balen. GEPATAR: A GEOTECHNICAL BASED PS-INSAR TOOLBOX FOR ARCHITECTURAL CONSERVATION IN BELGIUM. In International Geoscience and Remote Sensing Symposium (IGARSS), Texas, 2017. IEEE.
  3. S. Vanhuysse, T. Grippa, M. Lennert, E. Wolff, and M. Idrissa. Contribution of nDSM derived from VHR stereo imagery to urban land-cover mapping in sub-saharan africa. In 2017 Joint Urban Remote Sensing Event (JURSE), pages 1-4, March 2017.
  4. Manuel Campos-Taberner, Adriana Romero-Soriano, Carlo Gatta, Gustau Camps-Valls, Adrien Lagrange, Bertrand Le Saux, Annebeau Ere, Alexandre Boulch, Adrien Chan-Hon-Tong, Stephane Herbin, Hicham Randrianarivo, Marin Ferecatu, Michal Shimoni, Gabriele Moser, Devis Tuia, A Lagrange, B Le Saux, A Beaupére, A Boulch, A Chan-Hon-Tong, S Herbin, and H Randrianarivo. Processing of Extremely High-Resolution LiDAR and RGB Data: Outcome of the 2015 IEEE GRSS Data Fusion Contest–Part A: 2-D Contest. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 9(12):5547-5559, 2016.
  5. M Shimoni, R Haelterman, and P Lodewyckx. Advancing the retrievals of surface emissivity by modelling the spatial distribution of temperature in the thermal hyperspectral scene. In SPIE Defence and Security, Baltimore, 2016.
  6. A.-V Vo, L Truong-Hong, D F Laefer, D Tiede, S D 'oleire-Oltmanns, A Baraldi, M Shimoni, G Moser, and D Tuia. Processing of Extremely High Resolution LiDAR and RGB Data: Outcome of the 2015 IEEE GRSS Data Fusion Contest—Part B: 3-D Contest. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 9(12):5560-5575, 2016.
  7. Manuel Cubero-Castan, Jocelyn Chanussot, Veronique Achard, Xavier Briottet, and Michal Shimoni. A physics-based unmixing method to estimate subpixel temperatures on mixed pixels. IEEE Transactions on Geoscience and Remote Sensing, 53(4):1894-1906, 2015.
  8. M. Shimoni, R. Haelterman, and P. Lodewyckx. Data fusion for improving thermal emissivity separation from hyperspectral data. In International Geoscience and Remote Sensing Symposium (IGARSS). IEEE, 2015.
  9. M. Shimoni, J. Lopez, Y. Forget, E. Wolff, C. Michellier, T. Grippa, C. Linard, and M. Gilbert. An urban expansion model for African cities using fused multi temporal optical and SAR data. In International Geoscience and Remote Sensing Symposium (IGARSS), 2015.
  10. D. Borghys, M. Idrissa, M. Shimoni, O. Friman, M. Axelsson, M. Lundberg, and C. Perneel. Fusion of multispectral and stereo information for unsupervised target detection in very high resolution airborne data. In Proc. SPIE Signal Processing, Sensor Fusion, and Target Recognition XXII, SPIE Vol 8745, Baltimore, April 2013, 2013.
  11. Dirk C Borghys, Mahamadou Idrissa, Michal Shimoni, Ola Friman, Maria Axelsson, Mikael Lundberg, and Christiaan Perneel. Fusion of multispectral and stereo information for unsupervised target detection in VHR airborne data. In SPIE Defence and Security, Baltimore, 2013. SPIE.
  12. Manuel Cubero-Castan, Xavier Briottet, Véronique Achard, Michal Shimoni, and Jocelyn Chanussot. THE COMPARABILITY OF AGGREGATED EMISSIVITY AND TEMPERATURE OF HETEROGENEOUS PIXEL TO CONVENTIONAL TES METHODS. In IEEE Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), Gainesville, 2013.
  13. Alwin Dimmeler, Hendrik Schilling, Michal Shimoni, Dimitri Bulatov, and Wolfgang Middelmann. Combined Airborne Sensors in Urban Environment. In SPIE Defence and Security, Dublin, 2013.
  14. Ingmar Renhorn, Veronique Achard, Maria Axelsson, Koen Benoist, Dirk Borghys, Xavier Briottet, Rob Dekker, Alwin Dimmeler, Ola Friman, Ingebjørg Kåsen, Stefania Matteoli, Maria Lo Moro, Thomas Olsvik Opsahl, Mark Van Persie, Salvatore Resta, Hendrik Schilling, Piet Schwering, Michal Shimoni, Trym Vegard Haavardsholm, and Françoise Viallefont. Hyperspectral Reconnaissance in Urban Environment. In SPIE Defence and Security, Baltimore, 2013. SPIE.
  15. M Shimoni, R Haelterman, and C Perneel. SHORT TEMPORAL CHANGE DETECTION IN COMPLEX URBAN AREA. In International Geoscience and Remote Sensing Symposium (IGARSS), Melbourne, 2013. IEEE.
  16. M. Shimoni, M. Idrissa, D. Borghys, T. Haavardsholm, T-O. Opsahl, and C. Perneel. Urban features classification using 3D hyperspectral data. In 5th IEEE Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), Florida, USA, June 2013, 2013.
  17. Michal Shimoni, Mahamadou Idrissa, Dirk Borghys, Trym Haavardsholm, Thomas-Olsvik Opsahl, and Christiaan Perneel. URBAN FEATURES CLASSIFICATION USING 3D HYPERSPECTRAL DATA. In IEEE Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2013.
  18. D Borghys, V Achard, I Kasen, and C Perneel. Comparative evaluation of hyperspectral anomaly detection methods in scenes with diverse complexity. In Proc. OPTRO2012 Symposium on Optronics in Defence and Security, Paris, France, February 2012.
  19. D Borghys, A Bouaraba, and C Perneel. Activity Monitoring in a Commercial Harbor using Multitemporal Repeat-Pass {SAR} Data. In Proc. IGARSS, Munich, Germany, 2012.
  20. D Borghys, A Bouaraba, and C Perneel. Combination of different SAR modalities for geospatial intelligence applications in a harbor environment. In SPIE Proc. on Algorithms for Synthetic Aperture Radar Imagery XIX, volume 8394, Baltimore, USA, 2012.
  21. D Borghys, I Kasen, V Achard, and C Perneel. Comparative evaluation of hyperspectral anomaly detectors in different types of background. In SPIE Proc. on Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII, volume 8390, Baltimore, USA, 2012.
  22. Dirk Borghys, Ingebjørg Kå sen, Véronique Achard, and Christiaan Perneel. Hyperspectral Anomaly Detection: Comparative Evaluation in Scenes with Diverse Complexity. Journal of Electrical and Computer Engineering, 2012:1-16, 2012.
  23. A. Bouaraba, D. Borghys, A. Belhadj-Aissa, M. Acheroy, and D. Closson. IMPROVING CCD PERFORMANCE BY THE USE OF LOCAL FRINGE FREQUENCIES. Progress In Electromagnetics Research C, 32:123-137, 2012.
  24. Manuel Cubero-castan, Xavier Briottet, Michal Shimoni, Jocelyn Chanussot, and F-Saint Martin H. PHYSIC BASED AGGREGATION MODEL FOR THE UNMIXING OF TEMPERATURE AND OPTICAL PROPERTIES IN THE INFRARED DOMAIN Onera , the French Aerospace Lab , Toulouse 31055 , France Signal and Image Centre , Dept . of Electrical Engineering ( SIC-RMA ), 1000 Brussels ,. In IEEE Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), Lisbon, 2012. IEEE.
  25. N Gorelik, D Blumberg, S R Rotman, and D Borghys. Non-singular approximations for a singular covariance matrix . In SPIE Proc. on Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII, volume 8390, Baltimore, USA, 2012.
  26. Nir Gorelik, Dan Blumberg, Stanley R. Rotman, and Dirk Borghys. Target Detection Using Nonsingular Approximations for a Singular Covariance Matrix. Journal of Electrical and Computer Engineering, 2012:1-7, 2012.
  27. Ingmar Renhorn, Maria Axelsson, Koen Benoist, Dirk Bourghys, Yannick Boucher, Xavier Briottet, Sergio De Ceglie, Rob Dekker, Alwin Dimmeler, Remco Dost, Ola Friman, Ingebjørg Kåsen, Jochen Maerker, Mark van Persie, Salvatore Resta, Piet Schwering, Michal Shimoni, and Trym Vegard Haavardsholm. DETECTION IN URBAN SCENARIO USING COMBINED AIRBORNE IMAGING SENSORS. In SPIE Defence and Security, Baltimore, 2012.
  28. M Shimoni and C Perneel. DEDICATED CLASSIFICATION METHOD FOR THERMAL HYPERSPECTRAL IMAGING. In International Geoscience and Remote Sensing Symposium (IGARSS). IEEE, 2012.
  29. Michal Shimoni, Xavier Briottet, Manuel Cubero-castan, Christiaan Perneel, Véronique Achard, Jocelyn Chanussot, Onera Dota, Avenue Edouard Belin, F-Toulouse, and F-Saint Martin. PERFORMANCE ANALYSIS OF UNSUPERVISED UNMIXING MODELS FOR THERMAL HYEPSRPECTRAL. In IEEE Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), Beijin, 2012. IEEE.
  30. D Borghys, V Achard, I Kasen, and C Perneel. Evaluation of the sub-pixel performance of anomaly detectors. In 3rd IEEE Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), Lisbon, Portugal, June 2011.
  31. D Borghys, V Achard, S R Rotman, N Gorelik, and C Perneel. Hyperspectral anomaly detection: a comparative evaluation of methods. In Proc. XXX URSI General Assembly and Scientific Symp. of the Int. Union of Radio Science, Istanbul, Turkey, August 2011.
  32. M. Shimoni, X. Briottet, C. Perneel, B. Tanguy, Y. M. Frédéric, and E. Ben-Dor. Validation of physical unmixing model in the radiative domain. In Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing. IEEE, 2011.
  33. M Shimoni, M Crosetto, S Lang, P Bally, and F Boubila. The Independent Service Validation in GMES RESPOND: The Flood Validation Exercise. International Journal of Digital Earth, 11(1), 2011.
  34. M Shimoni, P Lagueux, C Perneel, and J-P Gagnon. Detection of occluded targets using thermal imaging spectroscopy. In NATO MSS. IEEE, 2011.
  35. M Shimoni, G Tolt, C Perneel, and J Ahlberg. DETECTION OF VEHICLES IN SHADOW AREAS. In IEEE, editor, IEEE Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), Lisbon, 2011.
  36. G Tolt, M Shimoni, and J Ahlberg. A SHADOW DETECTION METHOD FOR REMOTE SENSING IMAGES USING VHR HYPERSPECTRAL AND LIDAR DATA. In IEEE IGARSS, 2011.
  37. D Borghys and C Perneel. Study of the Influence of Pre-Processing on Local Statistics-Based Anomaly Detector Results. In 2nd IEEE Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), Reykjavik, Iceland, June 2010.
  38. M Shimoni, R Heremans, and C Perneel. DETECTION OF SMALL CHANGES IN COMPLEX URBAN AND INDUSTRIAL SCENES USING IMAGING SPECTROSCOPY. In International Geoscience and Remote Sensing Symposium (IGARSS). IEEE, 2010.
  39. M Shimoni, C Perneel, and J-P Gagnon. DETECTION OF OCCLUDED TARGETS USING THERMAL IMAGING SPECTROSCOPY. In IEEE, editor, IEEE Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), Reykjavik, 2010.
  40. D Borghys, E Truyen, M Shimoni, and C Perneel. Anomaly detection in complex environments: Evaluation of the inter- and intra-method consistency. In 1st IEEE Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, Grenoble, France, August 2009.
  41. D Borghys, E Truyen, M Shimoni, and C Perneel. Anomaly Detection in Hyperspectral Images of Complex Scenes. In Earsel Symposium, Chania, Greece, June 2009.
  42. M Shimoni, R Heremans, D Borghys, and C Perneel. Change Detection in Complex Industrial and Urban Scenes using VNIR and TIR Hyperspectral Imagery. In 6th EARSeL SIG IS Workshop, Tel Aviv, Israel, March 2009.
  43. D Borghys, Michal Shimoni, and C Perneel. Change detection in urban scenes by fusion of SAR and Hyperspectral data. In Remote Sensing for Environmental Monitoring, GIS Applications, and Geology VII, volume 6749, Florence, Italy, September 2007.
  44. D Borghys, Michal Shimoni, and C Perneel. Semi-Automatic Hyperspectral Image Classification of Urban Areas using Logistic Regression. In 1st EARSeL SIG Urban Remote Sensing Workshop Urban Remote Sensing - Challenges and Solutions, Berlin, GE, March 2006.
  45. D Borghys, Michal Shimoni, and C Perneel. Supervised classification of hyperspectral images using a combination of spectral and spatial information. In SPIE Conference on Image And Signal Processing for Remote Sensing XI; Bruges, volume 5982, September 2005.