Image denoising using local Wiener filter and its method noise

This paper proposed a new image denoising method on local Wiener filter. Firstly, nonsubsampled shearlet transform (NSST) is used to decompose noisy image since NSST is an effective multi-scale and multi-direction analysis tool in image processing. And then the high frequency NSST coefficients are denoised by a shrinkage function based on local Wiener filter. In this new shrinkage function, the method noise of local Wiener filter is employed effectively by using the Stein’s unbiased risk estimate and linear expansion of thresholds (SURE-LET) strategy. Finally, the inverse NSST is used to obtain the denoised image. Experimental results show that the proposed method is very good in performance compared to the state-of-the-art wavelet-based algorithms.