Infrared and Laser Engineering, Volume. 35, Issue 2, 234(2006)
Contourlet based image denoising using non-Gaussian bivariate model
References(7)
[1] [1] WAN G Sheng -qian,ZHO U Yuan -hua,ZOU Dao -wen.Adaptive shrinkage denoising using the neighborhood characteristic[J].Electronics Letters,2002,38(11):185-186.
[2] [2] WANG Sheng-qian,ZOU Dao-wen,DENG Cheng-zhi.Wavelet shrinkage threshold based on image singularity[C]//Int Conf Wavelet Analysis and Its Applications,Chongqing,2004:180-184.
[5] [5] DO M N,VETTERLI M.The contourlet transform:an efficient directional multiresolurion image representation[J].IEEE Transactions on Image Processing,2005,14(12):2091-2106.
[6] [6] Duncan D Y P,Minh N D.Directional Multiscale Modeling of Images using the Contourlet Transform[C]//In Statistical Signal Processing,IEEE Workshop,2003:262-265.
[7] [7] RAY S,MALLICK B K.A Bayesian transformation model for wavelets[J].IEEE Transactions on Image Processing,2003,12(12):1512-1521.
[8] [8] SENDUR L,SELESNICK I W.Bivariate shrinkage functions for wavelet based denoising exploiting interscale dependency[J].IEEE Trans Signal Processing,2002,50(11):2744-2756.
[9] [9] DONOHO D L,JOHNSTONE I M.Ideal spatial adaptation by wavelet shiinkage[J].Biometrika,1994,81 (3):425-455.
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[in Chinese], [in Chinese], [in Chinese]. Contourlet based image denoising using non-Gaussian bivariate model[J]. Infrared and Laser Engineering, 2006, 35(2): 234
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