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《Journal of Electronics and Information Technology》 2005-10
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Band Selection Using Divergence of Class-within PCA in Hyperspectral Images Classification

Huang Rui He Ming-yi (Shanxi Key Lab of Information Acquisition and Processing, Northwestern Polytechnical University, Xi 'an 710072, China)  
Band selection from multispectral or hyperspectral image data is an effective method to remove redundancy among bands and thus reduce dimension. An efficient algorithm using divergence based class-within principal component analysis (PCA) and analysis of corresponding coefficients is proposed. At first, the covariance of each class is diagonalized through PCA transforms on class data respectively, and then the divergence only depends on the summation of individual feature separability of transformed bands. Secondly, after an analysis of corresponding PCA transform coefficients, the candidate bands, original bands essential to classification, are determined by majority vote. At last, the final band subset is obtained by analyzing the dependency and divergence of bands in every subset generated according to the correlations of original band in candidates. Compared with sequential forward selection, the proposed method reduces the computation complexity, and encouraging results have been shown by experiments with an Airborne Visible/InfraRed Imaging Spectrometer (AVIRIS) data set.
【Fund】: 航空科学基金(01F53028)资助课题
【CateGory Index】: TP75;
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Chinese Journal Full-text Database 2 Hits
1 Zhao Chunhui,Chen Wanhai,Yang Lei(College of Information and Communication,Harbin Engineering University,Harbin 150001,China);Research advances and analysis of hyperspectral remote sensing image band selection[J];Journal of Natural Science of Heilongjiang University;2007-05
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Chinese Journal Full-text Database 10 Hits
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【Secondary References】
Chinese Journal Full-text Database 1 Hits
1 ZHAO Hong-yan,RAO Huan,ZHANG Zhang(The Scientific Academy of Land and Resource of Henan Province,Zhengzhou 450053,China);The Research about Urban Buildings Based on High Resolution Images[J];Geomatics & Spatial Information Technology;2008-06
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