Dr. Dirk C. Borghys Profile

Dr. Dirk C. Borghys

Research Scientist at Royal Military Academy

SPIE Involvement:

Author

Publications (16)

Proceedings Article | 11 June 2013 Paper

Paper

Hyperspectral reconnaissance in urban environment

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, Françoise Viallefont

Proceedings Volume 8704, 87040L (2013) https://doi.org/10.1117/12.2019348

KEYWORDS: Sensors, Target detection, Data modeling, Reflectivity, Ions, Image sensors, Roads, Spatial resolution, Image resolution, Calibration

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Proceedings Article | 23 May 2013 Paper

Paper

Fusion of multispectral and stereo information for unsupervised target detection in VHR airborne data

Dirk Borghys, Mahamadou Idrissa, Michal Shimoni, Ola Friman, Maria Axelsson, Mikael Lundberg, Christiaan Perneel

Proceedings Volume 8745, 874514 (2013) https://doi.org/10.1117/12.2015968

KEYWORDS: Mid-IR, Target detection, Image fusion, Sensors, Distortion, Image processing, Georeferencing, Cameras, 3D acquisition, Image resolution

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Proceedings Article | 31 May 2012 Paper

Paper

Detection in urban scenario using combined airborne imaging sensors

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, Trym Vegard Haavardsholm

Proceedings Volume 8353, 83530I (2012) https://doi.org/10.1117/12.921473

KEYWORDS: Sensors, Airborne remote sensing, Spatial resolution, Image sensors, Target detection, Defense and security, Spectral resolution, Environmental sensing, Infrared radiation, Thermography

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Proceedings Article | 24 May 2012 Paper

Paper

Nonsingular approximations for a singular covariance matrix

Nir Gorelik, D. Blumberg, Stanley Rotman, D. Borghys

Proceedings Volume 8390, 839021 (2012) https://doi.org/10.1117/12.915310

KEYWORDS: Principal component analysis, Detection and tracking algorithms, Target detection, Agriculture, Target acquisition, Data processing, Sensors, Matrices, Research management, Geography

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Proceedings Article | 24 May 2012 Paper

Paper

Comparative evaluation of hyperspectral anomaly detectors in different types of background

Dirk Borghys, Ingebjorg Kåsen, Veronique Achard, Christiaan Perneel

Proceedings Volume 8390, 83902J (2012) https://doi.org/10.1117/12.920387

KEYWORDS: Sensors, Target detection, Content addressable memory, Image segmentation, Principal component analysis, Detection and tracking algorithms, OSLO, Dimension reduction, Mahalanobis distance, Statistical analysis

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Proceedings Article | 3 May 2012 Paper

Paper

Combination of different SAR modalities for geospatial intelligence applications in a harbor environment

Dirk Borghys, Azzedine Bouaraba, Christiaan Perneel

Proceedings Volume 8394, 83940T (2012) https://doi.org/10.1117/12.918560

KEYWORDS: Synthetic aperture radar, Coherence (optics), Interferometry, Speckle, Artificial intelligence, Image classification, Data acquisition, Interferometric synthetic aperture radar, Satellites, Spatial resolution

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Proceedings Article | 29 September 2009 Paper

Paper

Comparison of algorithms for the classification of polarimetric SAR data

V. Alberga, D. Borghys, G. Satalino, D. Staykova, A. Borghgraef, F. Lapierre, C. Perneel

Proceedings Volume 7477, 74771V (2009) https://doi.org/10.1117/12.829756

KEYWORDS: Lawrencium, Scattering, Polarimetry, Synthetic aperture radar, Roads, Matrices, Image classification, L band, Sensors, Radar

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Proceedings Article | 12 November 2007 Paper

Paper

Change detection in urban scenes by fusion of SAR and hyperspectral data

Dirk Borghys, Michal Shimoni, Christiaan Perneel

Proceedings Volume 6749, 67490R (2007) https://doi.org/10.1117/12.738767

KEYWORDS: Synthetic aperture radar, Sensors, Image fusion, Polarimetry, Lawrencium, Roads, Data fusion, Speckle, Scattering, Image classification

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Urban areas are rapidly changing all over the world and therefore provoke the necessity to update urban maps frequently. Remote sensing has been used for many years to monitor these changes. The urban scene is characterized by a very high complexity, containing objects formed from different types of man-made materials as well as natural vegetation. Hyperspectral sensors provide the capability to map the surface materials present in the scene using their spectra and therefore to identify the main object classes in the scene in a relatively easy manner. However ambiguities persist where different types of objects are constructed of the same material. This is for instance the case for roads and roof covers. Although higher-level image processing (e.g. spatial reasoning) might be able to relief some of these constraints, this task is far from straight forward. In the current paper the authors fused information gathered using a hyperspectral sensor with that of high-resolution polarimetric SAR data. SAR data give information about the type of scattering backscatter from an object in the scene, its geometry and its dielectric properties. Therefore, the information obtained using the SAR processing is complementary to that obtained using hyperspectral data. This research was applied on a dataset consisting of hyperspectral data from the HyMAP sensor (126 channels in VIS-SWIR) and E-SAR data which consists of fullpolarimetric L-band and dual-polarisation (HH and VV) X-band data. Two supervised classifications are used; 'Logistic Regression' (LR) which applied to the SAR and the PolSAR data and a 'Matched Filter' which is applied to the hyperspectral data. The results of the classification are fused in order to improve the mapping of the main classes in the scene and were compared to a ground truth map that was constructed by combining a digital topographic map and a vectorized cadastral map of the research area. An adequate change detection of man-made objects in urban scenes was obtained by the fusion of features derived from SAR, PolSAR and hyperspectral data.

Proceedings Article | 19 October 2005 Paper

Paper

Supervised classification of hyperspectral images using a combination of spectral and spatial information

Dirk Borghys, Michal Shimoni, Christiaan Perneel

Proceedings Volume 5982, 59820E (2005) https://doi.org/10.1117/12.626817

KEYWORDS: Lawrencium, Distance measurement, Image classification, Principal component analysis, Hyperspectral imaging, Roads, Palladium, Target detection, Data acquisition, Roentgenium

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Proceedings Article | 12 January 2004 Paper

Paper

Combining multivariate statistics and speckle reduction for line detection in multichannel SAR images

Dirk Borghys, Christiaan Perneel, Aleksandra Pizurica, Wilfried Philips

Proceedings Volume 5236, (2004) https://doi.org/10.1117/12.510662

KEYWORDS: Speckle, Sensors, Synthetic aperture radar, L band, Roads, Image fusion, Polarimetry, X band, Radar, Spatial resolution

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Proceedings Article | 28 January 2002 Paper

Paper

Interpretation of multi-aspect high-resolution polarimetric SAR images

Dirk Borghys, Christiaan Perneel, Marc Acheroy

Proceedings Volume 4543, (2002) https://doi.org/10.1117/12.453958

KEYWORDS: Sensors, Image fusion, Synthetic aperture radar, Edge detection, Roads, Polarimetry, Spatial resolution, Buildings, L band, Statistical methods

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The aim of this article is to explore new methods to enhance the results of automatic interpretation of SAR images by combining images acquired from different viewing directions (multi-aspect SAR images). Using the combined information extracted from multi-aspect images allows to resolve problems of obscurance, by for instance the borders of a forest, to increase the resolution and to augment the confidence in detection as compared to detection in single images. The article focuses on high-resolution polarimetric images for the automatic interpretation of an airfield scene. Specifically for this type of images we have developed a set of new image interpretation tools such as edge detectors and bar (line) detectors, both based on multi-variate statistics. These detectors are briefly described in the article. The main part of the proposed article will focus on how the use of multi-aspect images can enhance the results of these detectors. The multi-aspect images are supposed to be accurately registered. It is thus possible to warp them into a common coordinate system. Because the spatial resolution of a SAR system is usually not the same in range and azimuth, it is sometimes better to detect objects in each image separately and fuse the results of the detection at the object level. This is particularly true for the detection and delimitation of the buildings. On the other hand, edge detectors can benefit from combined information on a pixel-level. In particular edge detectors based on multi-variate statistical methods can be applied on registered images, thus increasing the confidence level of detection and reducing the false alarm rate, by combining the information at a low level. For edge detectors we will compare results of combining the information available from multi-aspect polarimetric images at different levels. In particular we will compare the results of applying them directly to the registered image set with these obtained when applying them on each individual image and fusing the results at the object level or intermediate (edge-strength) level. Similar investigations will be presented for the bar detectors. Results will be shown on a set of polarimetric L-band images of an airfield.

Proceedings Article | 28 January 2002 Paper

Paper

Hierarchical approach for registration of high-resolution polarimetric SAR images

Dirk Borghys, Christiaan Perneel, Marc Acheroy

Proceedings Volume 4541, (2002) https://doi.org/10.1117/12.454148

KEYWORDS: Image registration, Synthetic aperture radar, Sensors, Roads, Image segmentation, Polarimetry, Edge detection, Dysprosium, 3D modeling, Image processing

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Proceedings Article | 21 December 2000 Paper

Paper

Contour detection in high-resolution polarimetric SAR images

Dirk Borghys, Christiaan Perneel, Marc Acheroy

Proceedings Volume 4173, (2000) https://doi.org/10.1117/12.410645

KEYWORDS: Sensors, Synthetic aperture radar, Speckle, Edge detection, Polarimetry, Radar, Image fusion, Image filtering, Reflectivity, Image registration

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SPIE Journal Paper | 1 February 1998

Multilevel data fusion for the detection of targets using multispectral image sequences

Dirk Borghys, Patrick Verlinde, Christiaan Perneel, Marc Acheroy

OE, Vol. 37, Issue 02, (February 1998) https://doi.org/10.1117/12.10.1117/1.601633

KEYWORDS: Image fusion, Target detection, Sensors, Image sensors, Detection and tracking algorithms, Data fusion, Infrared imaging, Sensor fusion, Infrared sensors, Databases

Proceedings Article | 28 July 1997 Paper

Paper

Long-range target detection in a cluttered environment using multisensor image sequences

Dirk Borghys, Patrick Verlinde, Christiaan Perneel, Marc Acheroy

Proceedings Volume 3068, (1997) https://doi.org/10.1117/12.280840

KEYWORDS: Sensors, Target detection, Image sensors, Detection and tracking algorithms, Motion estimation, Visualization, Motion detection, Infrared radiation, Image fusion, Infrared imaging

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Proceedings Article | 6 July 1994 Paper

Paper

Long-range automatic detection of small targets in sequences of noisy thermal infrared images

Dirk Borghys, Christiaan Perneel, Marc Acheroy

Proceedings Volume 2235, (1994) https://doi.org/10.1117/12.179102

KEYWORDS: Target detection, Detection and tracking algorithms, Sensors, Image segmentation, Infrared imaging, Thermography, Infrared radiation, Infrared detectors, Clouds, Motion models

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Showing 5 of 16 publications

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