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《Optical Technique》 2018-05
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Band selection method based on hyperspectral fundamental criterion

YAN Yang;HUA Wenshen;LIU Xun;CUI Zihao;Department of Electronic and Optical Engineering,Army Engineering University Shijiazhuang Campus;  
Hyperspectral data has the characteristics of many spectral bands,high dimensions and large amount of data.In order to improve the processing speed of hyperspectral data,it is necessary to reduce the dimension.Band selection is one of the basic methods of hyperspectral dimensionality reduction.A method based on correlation,information and inter-class separability in the hyperspectral bands is proposed.The intrinsic dimension of the hyperspectral image is determined by virtual dimension,and the subspace is divided according to the correlation coefficient between the bands.The maximum band index is calculated from each subspace using the discrete band index to form the subset.Simultaneously,in the subspace,the appropriate band of the largest separability factor is selected according to the separability criterion.The band subset is formed by the most suitable classification band that is selected by using the spectral angle match.So,the processing of reducing dimensions by band selection has been realized.The experimental results show that compared with the traditional optimal index and adaptive band selection method,the proposed method has improved the classification accuracy of hyperspectral images.
【CateGory Index】: TP751
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