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Spectral unmixing is one of the most challenging and fundamental problems in hyperspectral imagery. In this paper, we address a hyperspectral imagery unmixing problem by introducing sparse nonnegative matrix factorization unmixing algorithms into kernel space. Many sparse nonnegative matrix factorization algorithms has been recently applied to solve the hyperspectral unmixing problem because it overcome...
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