Fast image and video denoising via nonlocal means of similar neighborhoods

In this note, improvements to the non-local means image denoising method introduced in [2], [3] are presented. The original non-local 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, pre-classifying 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.

• Type: Journal
• Year: 2005
• Where: IEEE signal processing letters
• Authors: Mona Mahmoudi, Guillermo Sapiro
• Keywords: IEEE SIGNAL PROCESSING LETTERS 2005, Computational Complexity, Contexts, IEEE SIGNAL PROCESSING LETTERS 2005, Image And Video Denoising, Non-local Neighborhood Filters