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Spectral unmixing is an important technique of hyperspectral imagery processing. The traditional iterative processing of least squares linear spectral mixture analysis is of heavy computational burden. In this paper, a simple distance measure is proposed based on support vector machine (SVM). The method is free of iteration and dimensionality reduction,(More)
A new Hyperspectral image band selection algorithm based on maximal standard deviation is proposed to reduce spectral redundancy of Hyperspectral remote sensing image and computational complexity. It first uses standard deviation to measure the band information. The correlation between band and selecting band is then used as a weight factor for standard(More)
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