Neighboring adaptive BayesShrink image denoising in dual-tree complex wavelet transform
Wenwen Zhang · Computer Engineering and Applications Journal · 2012
In order to remove noise which is introduced by image acquisition or transmission more effectively,a neighboring adaptive Bayesian shrinkage image denoising method in dual-tree complex wavelet domain is proposed.This method makes use of the translation invariance and the advantage of more direction selective of the dual-tree complex wavelet transform,and the local adaptive neighborhood correlation of the coefficient is also considered.The variance of the corresponding coefficient of the appropriate neighborhood full inch window is estimated,the average of the variance which is used as the variance of the whole sub-band image is calculated using the sliding window.BayesShrink method is used to handle the wavelet coefficients to achieve efficient image denoising.The experimental results show that the proposed method gets higher PSNR and better visual expression.The denoising performance is excellent.