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

2023

2022

B. Koirala, Zahiri, Z., and Scheunders, P., A Robust Supervised Method for Estimating Soil Moisture Content From Spectral Reflectance, IEEE Transactions on Geoscience and Remote Sensing , vol. 60, pp. 1-13, 2022.PDF icon soil_moisture_content.pdf (7.95 MB)
P. Ghosh, Roy, S. Kumar, Koirala, B., Rasti, B., and Scheunders, P., Hyperspectral Unmixing Using Transformer Network, IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-16, 2022.PDF icon transformer_unmixing.pdf (6.32 MB)
B. Rast, Koirala, B., Scheunders, P., and Chanussot, J., MiSiCNet: Minimum Simplex Convolutional Network for Deep Hyperspectral Unmixing, IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-15, 2022.PDF icon ieee_journal_misicnet.pdf (11.02 MB)
P. Gosh, Roy, S. Kumar, Koirala, B., Rasti, B., and Scheunders, P., Hyperspectral Unmixing using Transformer Network, IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-16, 2022.PDF icon transformer_unmixing_author_version_to_upload.pdf (14.65 MB)

Pages