Entropic Descent Archetypal Analysis for Blind Hyperspectral Unmixing. (arXiv:2209.11002v2 [eess.IV] UPDATED)

In this paper, we introduce a new algorithm based on archetypal analysis for
blind hyperspectral unmixing, assuming linear mixing of endmembers. Archetypal
analysis is a natural formulation for this task. This method does not require
the presence of pure pixels (i.e., pixels containing a single material) but
instead represents endmembers as convex combinations of a few pixels present in
the original hyperspectral image. Our approach leverages an entropic gradient
descent strategy, which (i) provides better solutions for hyperspectral
unmixing than …

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