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

2024

B. Koirala, Rasti, B., Bnoulkacem, Z., and Scheunders, P., Nonlinear Spectral Unmixing Using Bézier Surfaces, IEEE Transactions on Geoscience and Remote Sensing, vol. 62, pp. 1-16, 2024.PDF icon nonlinear_spectral_unmixing_using_bezier_surfaces.pdf (9.66 MB)
B. Koirala, Rasti, B., and Scheunders, P., A Supervised Approach for Estimating Fractional Abundances of Binary Intimate Mixtures, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, pp. 1-11, 2024.PDF icon extensive_analysis_of_intimate_mixtures.pdf (4.49 MB)

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)

Pages