Opto-Electronic Engineering, Volume. 33, Issue 8, 108(2006)
Wavelet domain image denoising algorithm based on neighboring thresholding classification
[1] [1] DONOHO D.L,JOHNSTONE I.M.Ideal Spatial Adaptation via Wavelet Shrinkage[J].Biometrika,1994,81(3):425-455.
[2] [2] DONOHO D.L,JOHNSTONE I.M.Adapting To Unknown Smoothness via Wavelet Shrinkage[J].Journal of the American Statistical Assoc,1995,90(12):1200-1224.
[3] [3] CHANG S.G.,YU B VETTERLI M.Adaptive Wavelet Thresholding for Image Denoising and Compression[J].IEEE Trans.Image Processing,2000,9(9):1532-1546.
[4] [4] MIHCAK M.K.,Kozintsev I.,Ramchandran K.Spatially adaptive statistical modeling of wavelet image coefficients and its application to denoising[J].Proc.IEEE Int.Conf.Acoust.Speech,and Signal Proc,1999,6:3253-3256.
[5] [5] CHANG S.G.,Yu B VETTERLI M.Spatially adaptive wavelet thresholding with context modeling for image denoising[J].IEEE Trans.Image Processing,2000,9(9):1522-1531.
[6] [6] T.Tony CAI,Bernard W.SILVERMAN.Incorporating information on neighbouring coefficients into wavelet estimation[J].Sankhya:The Indian Journal of Statistics,2001,63(2):127-148.
[7] [7] SHENGQIAN W,YUANHUA Z,DAOWEN Z.Adaptive shrinkage denoising using neighbourhood characteristic[J].IEE Electronics Letters,2002,38(11):502-503.
[8] [8] RAHMAN S.M,HASAN M.K.Wavelet-domain iterative center weighted median filter for image denoising[J].Signal Processing,2003,83(5):1001-1012.
Get Citation
Copy Citation Text
[in Chinese], [in Chinese], [in Chinese], [in Chinese]. Wavelet domain image denoising algorithm based on neighboring thresholding classification[J]. Opto-Electronic Engineering, 2006, 33(8): 108