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- W2078657074 abstract "This paper proposes a new technique for hyperspectral band selection from the spectral similarity perspective. Through a newly defined measure for band subset discriminativeness, class-specific important bands are retained which can preserve the spectral similarity of the samples from the same class and narrow down candidate band subset for the following search procedure. Then optimal search is performed in the aggregated band subset from all classes. Experiments on the Indian Pine benchmark data set have proved the efficiency and effectiveness of the proposed method." @default.
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- W2078657074 date "2013-07-01" @default.
- W2078657074 modified "2023-09-23" @default.
- W2078657074 title "Hyperspectral band selection from the spectral similarity perspective" @default.
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- W2078657074 doi "https://doi.org/10.1109/igarss.2013.6721179" @default.
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