Image and Signal Processing Methods

Hyperspectral band selection based on triangular factorization

[+] Author Affiliations
Wenqiang Zhang, Xiaorun Li

Zhejiang University, Department of Electric Engineering, Zhejiang Province, China

Liaoying Zhao

Hangzhou Dianzi University, Department of Computer Science, Zhejiang Province, China

J. Appl. Remote Sens. 11(2), 025007 (May 04, 2017). doi:10.1117/1.JRS.11.025007
History: Received January 16, 2017; Accepted April 13, 2017
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Abstract.  We proposed an efficient unsupervised band selection method, maximum ellipsoid volume triangular factorization (MEV–TF), which is based on MEV and TF. MEV band selection regards the bands with the maximum determinant of the covariance matrix as the optimal band collection. By adopting TF, MEV–TF replaces the matrix determinant with scalar multiplication and achieves incremental calculation, which decreases the computational cost significantly. MEV–TF tries to select bands with large information and low correlation. Experimental results on different real data verify the efficiency of the proposed method.

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Citation

Wenqiang Zhang ; Xiaorun Li and Liaoying Zhao
"Hyperspectral band selection based on triangular factorization", J. Appl. Remote Sens. 11(2), 025007 (May 04, 2017). ; http://dx.doi.org/10.1117/1.JRS.11.025007


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