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Linear unmixing-based compressive sensing has been extensively exploited for hyperspectral image (HSI) compression in recent years among which gradient sparsity is widely used to characterize the spatial continuity of abundance matrix given a small amount of endmembers. Though these methods have achieved good reconstruction results, identifying necessary endmembers from an HSI is challenging for them...
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