Abstract-In this letter, improvements to the nonlocal means image denoising method introduced by Buades et al. are presented. The original nonlocal means method replaces a noisy pixel by the weighted average of pixels with related surrounding neighborhoods. While producing state-of-the-art denoising results, this method is computationally impractical. In order to accelerate the algorithm, we introduce filters that eliminate unrelated neighborhoods from the weighted average. These filters are based on local average gray values and gradients, preclassifying neighborhoods and thereby reducing the original quadratic complexity to a linear one and reducing the influence of less-related areas in the denoising of a given pixel. We present the underlying framework and experimental results for gray level and color images as well as for video. Index Terms-Computational complexity, contexts, image and video denoising, nonlocal neighborhood filters.
Another accelerating method is proposed by Mahmoudi and Sapiro REF via eliminating unrelated neighborhoods from the weighted average.
Fast image and video denoising via nonlocal means of similar neighborhoods
IEEE Signal Processing Letters
IEEE Signal Processing Letters
Mathematics Computer Science