Remote Sensing

Remote Sensing is the research area in which 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. Main application domains are vegetation monitoring for which we collaborate with the Teleprocessing group of VITO (Flemish Institute for Technological Research).

Journal publications



A. J. Rebelo, Scheunders, P., Esler, K. J., and Meire, P., Evaluating palmiet wetland decline: a comparison of three methods, Remote Sensing Applications: Society and Environment, vol. 8, pp. 212-223, 2017.
R. Luo, Liao, W., Zhang, H., Zhang, L., Pi, Y., Scheunders, P., and Philips, W., Fusion of Hyperspectral and LiDAR Data for Classification of Cloud-Shadow Mixed Remote Sensing Scene, IEEE-JSTARS, Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 10, no. 8, pp. 3768-3781, 2017.
R. Heylen, Parente, M., and Scheunders, P., Estimation of the number of endmembers in a hyperspectral image via the hubness phenomenon, IEEE Transactions on Geoscience and Remote Sensing, vol. 55, no. 4, pp. 2191-2200, 2017.