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

2021

B. Rasti, Koirala, B., Scheunders, P., and Ghamisi, P., UnDIP: hyperspectral unmixing using deep image prior, IEEE Transactions on Geoscience and Remote Sensing, pp. 1-15, 2021.
T. Hu, Li, W., Liu, N., Tao, R., Zhang, F., and Scheunders, P., Hyperspectral Image Restoration Using Adaptive Anisotropy Total Variation and Nuclear Norms, IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 2, pp. 1516-1533, 2021.

2020

2019

R. Heylen, Andrejchenko, V., Zahiri, Z., Parente, M., and Scheunders, P., Nonlinear hyperspectral unmixing with graphical models, IEEE Transaction on Geoscience and Remote Sensing, vol. 57, no. 7, pp. 4844-4856, 2019.

2018

Pages