Joint distribution of nonsubsampled contourlet domain and its application to texture retrieval

Yi Zheng; Zhiguo Cao; Wen Zhuo; Yang Xiao

doi:10.1117/12.833154

30 October 2009 Joint distribution of nonsubsampled contourlet domain and its application to texture retrieval

Yi Zheng, Zhiguo Cao, Wen Zhuo, Yang Xiao

Proceedings Volume 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications; 74984V (2009) https://doi.org/10.1117/12.833154
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

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.

Citation Download Citation

Yi Zheng, Zhiguo Cao, Wen Zhuo, and Yang Xiao "Joint distribution of nonsubsampled contourlet domain and its application to texture retrieval", Proc. SPIE 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications, 74984V (30 October 2009); https://doi.org/10.1117/12.833154

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