Superpixel-Guided Local Sparsity Prior for Hyperspectral Sparse Regression Unmixing
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DOI: 10.1109/lgrs.2022.3218730
Abstract: Sparse regression relaxes the difficulties of blind unmixing of hyperspectral data thanks to the spectral library. Many investigations, however, attach importance to global priors such as sparsity and low rankness. This letter proposes a local-global-based… read more here.
Keywords: sparsity; sparse regression; local sparsity; regression unmixing ... See more keywords