Learning Endmember Dynamics In Multitemporal Hyperspectral Data Using A State-Space Model Formulation

Hyperspectral image unmixing is an inverse problem aiming at recovering the spectral signatures of pure materials of interest (called endmembers) and estimating their proportions (called abundances) in every pixel of the image. However, in spite of a trem
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