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Remote sensing

Multispectral and hyperspectral satellite and aerial image processing and analysis

UnDIP: hyperspectral unmixing using deep image prior

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.

UnDIP: hyperspectral unmixing using deep image prior

B. Rasti, Koirala, B., Ghamisi, P., and Scheunders, P., “UnDIP: hyperspectral unmixing using deep image prior”, IEEE Transactions on Geoscience and Remote Sensing, pp. 1-15, 2021.

Data Fusion Using a Multi-Sensor Sparse-Based Clustering Algorithm

K. Rafiezadeh Sahi, Ghamisi, P., Rasti, B., Jackisch, R., Scheunders, P., and Gloaguen, R., “Data Fusion Using a Multi-Sensor Sparse-Based Clustering Algorithm”, Remote Sensing, vol. 12 (23), no. 4007, 2020.

Robust supervised method for nonlinear spectral unmixing accounting for endmember variability

B. Koirala, Zahiri, Z., Lamberti, A., and Scheunders, P., “Robust supervised method for nonlinear spectral unmixing accounting for endmember variability”, IEEE Transactions on Geoscience and Remote Sensing, 2020.

Hyperspectral Image Restoration Using Adaptive Anisotropy Total Variation and Nuclear Norms

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.

How Hyperspectral Image Unmixing and Denoising Can Boost Each Other

B. Rasti, Koirala, B., Scheunders, P., and Ghamisi, P., “How Hyperspectral Image Unmixing and Denoising Can Boost Each Other”, Remote Sensing, vol. 12, no. 1728, 2020.

A Machine Learning Framework for Estimating Leaf Biochemical Parameters From Its Spectral Reflectance and Transmission Measurements

B. Koirala, Zahiri, Z., and Scheunders, P., “A Machine Learning Framework for Estimating Leaf Biochemical Parameters From Its Spectral Reflectance and Transmission Measurements”, IEEE Transactions on Geoscience and Remote Sensing, vol. 58, no. 10, pp. 7393-7405, 2020.

A spectral mixing model accounting for multiple reflections and shadow

V. Andrejchenko, Zahiri, Z., Heylen, R., and Scheunders, P., “A spectral mixing model accounting for multiple reflections and shadow”, in IGARSS 2019, International Geoscience and Remote Sensing Symposium, Yokohama, Japan, 2019, pp. 286-289.

Analysis of hyperspectral images for detection of drought stress and recovery in maize plants in a high-throughput phenotyping platform

M. Shahrimie Asaari, Mertens, S., Dhondt, S., Inze, D., Wuyts, N., and Scheunders, P., “Analysis of hyperspectral images for detection of drought stress and recovery in maize plants in a high-throughput phenotyping platform”, Computers and Electronics in Agriculture, vol. 162, pp. 749-758, 2019.

Automatic Detection of Surface Damages on Steel Structures using Near Infrared Hyperspectral Imaging

Z. Zahiri, Ribbens, B., Vanlanduit, S., and Scheunders, P., “Automatic Detection of Surface Damages on Steel Structures using Near Infrared Hyperspectral Imaging”, 9th Workshop on Hyperspectral Image and Signal Processing : Evolution in Remote Sensing (WHISPERS). 2018.

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