Method of Image Denoising Based on Statistical Mixture Model in Wavelet Domain

Chang S, Yu B, Vetterli M. Adaptive wavelet thresholding for image denoising and compression[J].IEEE Trans. on Image Processing.2000, 9(9):1532-1546[2]Crouse M S, Nowak R D. Wavelet-based signal processing using hidden Markov models[J].IEEE Trans. on Signal Processing.1998, 46(4):886-902[3]Lewis A S, Knowles G. Image compressing using the 2-d wavelet transform. IEEE Trans. on Image Processing, 1992, 1(2): 224-250.[4]Liu J, Moulin P. Information-theoretic analysis of interscale and intrascale dependencies between image wavelet coefficients[J].IEEE Trans. on Image Processing.2001, 10(11):1647-1658[5]Simoncelli E P, Adelson E H. Noise removal via Bayesian wavelet coring. In Proc. IEEE Int. Conf. on Image Processing, Lausanne, Switzerland, 1996, 1: 379-382.[6]Donoho D L, Johnstone I M. Ideal spatial adaptation via wavelet shrinkage[J].Biometrika.1994, 81(3):425-455[7]Donoho D L, Johnstone I M. Adapting to unknown smoothness[8]via wavelet shrinkage. Journal of American Statistical Assoc., 1995, 90(432): 1200-1224.[9]Rombery J K.[J].Choi H, Baraniuk R G. Hidden Markov tree modeling of complex wavelet transforms. In Proc. IEEE ICASSP 00, Istanbul, Turkey.2000,:-[10]Kingsbury N G. The dual-tree complex wavelet transform: a new efficient tool for image restoration and enhancement. In Proc. EUSIPCO 98, Island of Rhodes, Greek, 1998: 319-322.[11]Kingsbury N G. A dual-tree complex wavelet transform with improved orthogonality and symmetry properties. In Proc. IEEE Int. Conf. on Image Processing, Vancouver, Canada, 2000, 2: 375-378.[12]Sendur I, Selesnick I W. Bivariate shrinkage function for wavelet-based denoising exploiting interscale dependency[J].IEEE Trans. on Signal Processing.2002, 50(11):2744-2756