Non-Local Means Denoising
The Non-Local Means (NLM) algorithm for image denoising differs fundamentally from local mean filtering approaches. Unlike traditional methods that average pixels within a local neighborhood of the target pixel, NLM calculates weighted averages across all image pixels based on similarity measures between pixel neighborhoods. This approach preserves finer image details while reducing noise, resulting in superior sharpness retention compared to local mean algorithms. Implementation typically involves patch comparison, distance metric computation, and weighting function application.