Shape and Contrast Adaptive Non-local Means Filter

In this paper we propose an improvement to the NLM algorithm. It consists of an adaptive threshold parameter used to compute the similarity function of the Non-Local Means (NLM) approach integrated in the NLM-SAP (shape-adaptive-patches) algorithm. To obtain the adaptive threshold parameter we use an algorithm that decomposes the image in a textural and a homogenous part. Additionally, a prefiltering method is used on the input noisy image, that is based on a discrete version for TV filtering. Experimental results show that this allows the obtention of better visual, and objective measures-quantified results than our previous work and other considered NLM approaches. In some cases, better visual results were obtained compared with the state-of-the-art BM3D (Block Matching 3D) algorithm and the results in terms of PSNR/MSSIM are comparable.