Hyperspectral Unmixing via L 1/2 Sparsity-Constrained Nonnegative Matrix Factorization
Hyperspectral unmixing is a crucial preprocessing step for material classification and recognition. In the last decade, nonnegative matrix factorization (NMF) and its extensions have been intensively studied to unmix hyperspectral imagery and recover the
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|Source:||IEEE Transactions on Geoscience and Remote Sensing|
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