Abstract
Block matching 3D denoising (BM3D) is an excellent single-image denoising method. However, it still needs to be improved for solving practical problems. In this study, the authors attempt to improve the method of BM3D. First, one of the problems of BM3D is that some of its references cannot perform self-adaption when the noise intensity of the images is changed. Therefore, they propose a method using total variation (TV) to calculate the image noise intensity and make the references perform self-adaption. Second, finding similar blocks in the BM3D method is a time-consuming procedure. To solve this problem, they analyse the relationship between the numbers of similar blocks and denoising effect, improve the process of searching for similar blocks, and reduce the running time. Third, through the experiment they find that the denoising effect of BM3D method in the domain of complex texture is unsatisfactory. Thus, they proposed a hybrid denoising method for the complex texture area, using the new TV model and BM3D method together to restore the image. Their experimental results show that the improved BM3D method performs better than the original BM3D method.
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