Improvement of BM3D Algorithm Based on Wavelet and Directed Diffusion
Block-matching and 3D filtering (BM3D) has showngreat power for image denoising. By decomposing the BM3Drestored image into three orthogonal subbands, we find thatthe subband of the high-frequency component, of which thewavelet coefficients are less than a given threshold, has madesome true textures of the original image lost and, the PSNR ofthe restored image is pulled down. Therefore, in this paper, wepropose a modified BM3D algorithm to solve these problems. We diffuse the subband of the high-frequency component, ofwhich the wavelet coefficients are less than the threshold of theBM3D restored image to the corresponding subband of thenoisy image to get a new estimate by using an improveddirected diffusion equation model. The Laplace operator isreplaced by an anisotropic diffusion operator and two differentcoefficients are added in the two diffusion terms. By replacingthe corresponding subband of the BM3D restored image withthe new estimate, we obtain the improved denoising result. Experimental results demonstrate that the proposed methodachieves better performance than original BM3D algorithm interms of both removing noise and persevering the edges anddetails of the image.