Hyperspectral Unmixing Based on Nonnegative Matrix Factorization: A Comprehensive Review. (arXiv:2205.09933v1 [cs.CV])

Hyperspectral unmixing has been an important technique that estimates a set
of endmembers and their corresponding abundances from a hyperspectral image
(HSI). Nonnegative matrix factorization (NMF) plays an increasingly significant
role in solving this problem. In this article, we present a comprehensive
survey of the NMF-based methods proposed for hyperspectral unmixing. Taking the
NMF model as a baseline, we show how to improve NMF by utilizing the main
properties of HSIs (e.g., spectral, spatial, and structural information). We
categorize three …

arxiv cv factorization review