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A survey of band selection techniques for hyperspectral image classification
2020
Journal of Spectral Imaging
Hyperspectral images usually contain hundreds of contiguous spectral bands, which can precisely discriminate the various spectrally similar classes. However, such high-dimensional data also contain highly correlated and irrelevant information, leading to the curse of dimensionality (also called the Hughes phenomenon). It is necessary to reduce these bands before further analysis, such as land cover classification and target detection. Band selection is an effective way to reduce the size of
doi:10.1255/jsi.2020.a5
fatcat:cvibjoofbbd6jpu4ij626wigdy