Texture image segmentation method based on wavelet packet transform and FCM clustring

[1] Stephane G, Mallat A. Theory for multiresolution signal decomposition: the wavelet representation [J]. IEEE Trans on Pattern Analysis and Machine Intelligence, 1989,6: 674 - 693 [2] Brady K, Jermyn I H, Zerubia J. Texture analysis: anadaptive probabilistic approach Proc IEEE ICIP. Barcelona, Spain:IEEE, 2003: 1045-1048 [3] Herley Cormac, Xiong Zixiang, Ramchandran Kannan, et al. Joint space frequency segmentation using balanced wavelet packet trees for least-cost image representation[J]. IEEE Trans on Image Processing, 1997,6(9):1213-1229 [4] Soo Chang Kim. Tae jin kang texture classification and segmentation using incomplete tree structured wavelet packet frame and gaussian mixture model IEEE International Workshop on Imaging Systems and Techniques. Niagara Falls:IEEE,2005,5:46-51 [5] Rahul Shukla, Pier Luigi Dragotti, Minh N Do,et al. Rate-distortion optimized tree-structured compression algorithms for piecewise polynomial images[J]. IEEE Trans on Image Processing, 2005,3:343-359 [6] Unser M. Texture classification and segmentation using wavelet frames[J]. IEEE Transactions On Signal Processing,1995,4 (11):1549-1560 [7] 吴高洪,章毓晋,林行刚.利用小波变换和特征加权进行纹理分割[J].中国图象图形学报,2001,4:334-337 Wu Gaohong, Zhang Yujin, Lin Xinggang. Texture segmentation with wavelet transform and feature weighting[J].Journal of Image and Graphics, 2001,4:334-337(in Chinese) [8] Xie X L, Beni G. A validity measure for fuzzy clustering[J]. IEEE Trans on Pattern Analysis and Machine Intelligence,1991, 13: 841-847