Center pixel weight based on Wiener filter for non-local means image denoising

In non-local means (NLM) method for image denoising, the weight of the center pixel is called the center weight (CW). The CW plays an important role for the performance of NLM. This paper proposes a novel CW by studying the relation between Perona-Malik anisotropic diffusion (PMAD) and NLM. The proposed CW is called the Wiener filter center weight (WFCW) since Wiener filter is introduced in the proposed CW computation. At the same time, the relation between non-local total variation and NLM is further disclosed. Test results show that the proposed method can achieve better results and is very efficient compared with the related NLM methods.