Non-local means filter is an efficient and brilliant approach as it extends the scope from neighborhood to global area. The average of only those pixels is considered who belong similar to the patches in the whole image. I want to understand whether it can handle Gaussian noises effectively? And is it better than Bilater Filters?
A bilateral filter is used for smoothening images and reducing noise, while preserving edges. Whereas non-local means (NLM) algorithm replaces the value of a pixel by an average of a selection of other pixels values: small patches centered on the other pixels are compared to the patch centered on the pixel of interest, and the average is performed only for pixels that have patches close to the current patch. As a result, this algorithm can restore well textures, that would be blurred by other denoising algorithm.