Web: http://arxiv.org/abs/2209.11002

Sept. 23, 2022, 1:14 a.m. | Alexandre Zouaoui (1), Gedeon Muhawenayo (1), Behnood Rasti (2), Jocelyn Chanussot (1), Julien Mairal (1) ((1) Thoth, Inria, UGA, CNRS, Grenoble INP,

cs.CV updates on arXiv.org arxiv.org

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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