Remote Sensing

Remote Sensing is the research area in which the Earth's surface is studied, usually using the reflectance spectrum of the Sun. Vision Lab has built expertise in the processing and analysis of multispectral and hyperspectral remote sensing images. Topics of research include the development of techniques for image denoising, restoration, fusion, segmentation, classification and spectral unmixing. Recently, research is shifted to more close-range applications, for which we have our own acquisition equipement (spectrometer 400-2500 nm; VNIR camera 400-900 nm and SWIR camera 1000-1700 nm). Applications are material characterization (corrosion, soil moisture, powder material composition).

Journal publications

2016

A. Karami, Heylen, R., and Scheunders, P., “Hyperspectral Image Compression Optimized for Spectral Unmixing”, IEEE Transactions on Geoscience and Remote Sensing, vol. pp, no. 99, 2016.
G. Thoonen, Nys, B., Haegen, V. Y., Roy, D. G., and Scheunders, P., “Automatic forensic analysis of automotive paints using optical microscopy”, Forensic Science International, vol. 259, pp. 210-220, 2016.
R. Heylen and Scheunders, P., “A multilinear mixing model for nonlinear spectral unmixing”, IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 1, pp. 240-251, 2016.

2015

A. Karami, Heylen, R., and Scheunders, P., “Band-specific Shearlet-based Hyperspectral Image Noise Reduction”, IEEE Transaction Geosciences and Remote Sensing , vol. 53, no. 9, 2015.
R. Heylen, Scheunders, P., Gader, P., and Rangarajan, A., “Nonlinear unmixing by using different metrics in a linear unmixing chain”, IEEE-JSTARS, Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2015.
M. A. Akhter, Heylen, R., and Scheunders, P., “A geometric matched filter for hyperspectral target detection and partial unmixing”, IEEE Geoscience and Remote Sensing letters, vol. 12, pp. 661-665, 2015.
L. Tits, Heylen, R., Somers, B., Scheunders, P., and Coppin, P., “A geometric unmixing concept for the selection of optimal binary endmember combinations”, IEEE Geoscience and Remote Sensing letters, vol. 12, pp. 82-86, 2015.

2014

D. Burazerovic, “Advances in unmixing of hyperspectral remote sensing imagery”, 2014.
D. Burazerovic, Heylen, R., Raymaekers, D., Knaeps, E., and Scheunders, P., “A spectral-unmixing approach to estimate water-mass concentrations in case-II waters”, IEEE-JSTARS, Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, 2014.
R. Heylen and Scheunders, P., “A distance geometric framework for non-linear hyperspectral unmixing”, IEEE-JSTARS, Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, pp. 1879-1888, 2014.

Pages