Total variation and &#x2113;<inf>q</inf> based hyperspectral unmixing for feature extraction and classification

Abstract

Blind hyperspectral unmixing jointly estimates both the endmembers and the abundances of hyperspectral images. The endmembers represent the spectral signatures of material found in the image and the abundances specify the amount of each material seen in each pixel in the image. In this paper, a blind hyperspectral unmixing method for feature extraction and… (More)
DOI: 10.1109/IGARSS.2015.7325794

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