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Band clustering and selection and decision fusion for target detection in hyperspectral imagery

  • Beihang University

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

A band clustering and selection approach based on a hyperspectral measure, spectral information divergence (SID) is presented in this paper. Hyperspectral image data is analyzed for target detection. Hyperspectral image data and spectral signatures of the targets are used to measure the SID. Virtual dimensionality (VD) is used to select optimal number of bands. For endmember extraction, vertex component analysis (VCA) is used. For decision fusion a new approach based on spectral discriminatory entropy (SDE) is proposed. A comparative study is conducted to show the effectiveness of new approach of band clustering and selection. Decision fusion is also compared with full band and individual SID detection schemes.

源语言英语
主期刊名2009 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings, ICASSP 2009
1101-1104
页数4
DOI
出版状态已出版 - 2009
活动2009 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009 - Taipei, 中国台湾
期限: 19 4月 200924 4月 2009

出版系列

姓名ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN(印刷版)1520-6149

会议

会议2009 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009
国家/地区中国台湾
Taipei
时期19/04/0924/04/09

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