BayesShrink is one of the best algorithms for wavelet thresholding denoising

while WienerChop improves VisuShrink by Wiener filtering in wavelet domain. We studied the denoising method uniting BayesShrink and WienerChop. The combined algorithm has smaller mean squared erroe(MSE) and higher signal to noise ratio(SNR) than BayesShrink or WienerChop. It integrates the advantages of the two algorithms

and improves the problems which images are smoothed overly by WienerChop and BayesShrink retains some noise artifacts. It can visually obtain more pleasing denoised images.