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Acoustics, Speech, and Signal Processing, IEEE International Conference on (2009)
Taipei, Taiwan
Apr. 19, 2009 to Apr. 24, 2009
ISBN: 978-1-4244-2353-8
pp: 1101-1104
Ihsan ul Haq , School of Electronic and Information Engineering, Beijing University of Aeronautics and Astronautics, 100191, China
Xiaojian Xu , School of Electronic and Information Engineering, Beijing University of Aeronautics and Astronautics, 100191, China
Aamir Shahzad , School of Electronic and Information Engineering, Beijing University of Aeronautics and Astronautics, 100191, China
ABSTRACT
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.
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CITATION

A. Shahzad, I. u. Haq and Xiaojian Xu, "Band clustering and selection and decision fusion for target detection in hyperspectral imagery," Acoustics, Speech, and Signal Processing, IEEE International Conference on(ICASSP), Taipei, Taiwan, 2009, pp. 1101-1104.
doi:10.1109/ICASSP.2009.4959780
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