Multi-stage Block-Matching Transform Domain Filtering for Image Denoising

In order to further improve the image denoising performance of the nonlocal transform domain filtering method,this paper proposes a multistage block matching transform domain filtering method.First,it finds some similar image blocks in the noisy image through the block matching,and then implements the 1D Haar wavelet transform among these similar image blocks,uses hard threshold shrinkage to transform coefficient for image denoising.Because the number of similar image blocks is limited in a single image,only one step above operations can not completely remove the noise in the image,so residual noise is removed by iteration strategy.Experimental results show that the denoising results of the proposed method are better than those of block matching 3D filtering method on both of PSNR and subjective visual quality.