A Video Denoising Method with 3D Surfacelet Transform Based on Block matching and Grouping

This paper proposes a novel video denoising method combining block matching based on the E3SS and grouping these blok strategy, 3D Surfacelet transform. Firstly, we utilize the SAD standard and E3SS search algorithm which we proposed by searching all frames for blocks which are similar to the currently processed one. Secondly, the matched blocks are stacked together to form some new 3D Sub-video sequence and because of the similarity between them, the data in the video array exists high level of correlation. We apply the 3D surfacelet transform to them and effectively attenuate the noise by solid threshold shrinkage of the 3D transform coefficients. Finally, inversely transforming the coefficients and obtaining the denoising video. This algorithm is obviously better than other 3D method in the denoising effect and the PSNR is increased about 0.9 dB. In terms of visual quality, the proposed method can effectively preserve the video detail, and the trajectory of motion object is very smooth, which is especially adequate to process the video flames with acute movement and plenty of large area movement object and background movement.