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Proceedings Paper

Joint distribution of nonsubsampled contourlet domain and its application to texture retrieval
Author(s): Yi Zheng; Zhiguo Cao; Wen Zhuo; Yang Xiao
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Paper Abstract

In this paper, the joint distribution of the Nonsubsampled Contourlet Transform coefficients is studied. It is found that the estimation of the joint distribution is implement impossible due to the complex of joint empirical distribution function and dependence of NSCT coefficient vector components. To distinguish different joint distributions of different images, the sample covariance matrix feature is proposed. The texture retrieval experiment is conducted in order to evaluate the performance of the sample covariance matrix feature. The result shows that the proposed feature is efficient in representing the texture and the difference of the joint distribution of the Nonsubsampled Contourlet Transform coefficients.

Paper Details

Date Published: 30 October 2009
PDF: 5 pages
Proc. SPIE 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications, 74984V (30 October 2009); doi: 10.1117/12.833154
Show Author Affiliations
Yi Zheng, Huazhong Univ. of Science and Technology (China)
Zhiguo Cao, Huazhong Univ. of Science and Technology (China)
Wen Zhuo, Huazhong Univ. of Science and Technology (China)
Yang Xiao, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 7498:
MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications
Faxiong Zhang; Faxiong Zhang, Editor(s)

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