Congratulations to our labmates and collaborators: Ricardo Augusto Borsoi, Tales Imbiriba, Jose Carlos Moreira Bermudez, Cedric Richard, Jocelyn Chanussot, Lucas Drumets, Jean-Yves Tourneret, Alina Zare and Christian Jutten! Their publication, “Spectral Variability in Hyperspectral Data Unmixing: A Comprehensive Review” was… Read More
Tag: spectral variability
Multi-Target Multiple Instance Learning for Hyperspectral Target Detection
Abstract: In remote sensing, it is often challenging to acquire or collect a large dataset that is accurately labeled. This difficulty is usually due to several issues, including but not limited to the study site’s spatial area and accessibility, errors… Read More
Spectral Variability in Hyperspectral Data Unmixing: A Comprehensive Review
Abstract: The spectral signatures of the materials contained in hyperspectral images (HI), also called endmembers (EM), can be significantly affected by variations in atmospheric, illumination or environmental conditions typically occurring within an HI. Traditional spectral unmixing (SU) algorithms neglect the… Read More