Non-Local Means Filter

The Non-Local Means Filter is an image smoothing technique that takes an input image along with three parameters: search window radius (t), similarity window radius (f), and smoothing parameter (h). The method is typically implemented through function calls like NLmeans(ima, 5, 2, sigma).

This filter operates on the principle of image similarity-based smoothing. It works by identifying pixels similar to the current pixel within a search window and computing their weighted average for smoothing. The search window size is determined by parameter t, while the similarity comparison area is controlled by parameter f. The smoothing parameter h regulates the smoothing intensity - higher values result in more aggressive smoothing. The algorithm calculates Euclidean distances between pixel neighborhoods to determine similarity weights.

The function call NLmeans(ima, 5, 2, sigma) demonstrates practical implementation where 'ima' represents the input image, '5' defines the search window radius, '2' sets the similarity window radius, and 'sigma' specifies the smoothing parameter. The implementation typically involves nested loops for window processing and Gaussian-weighted similarity computations.

By employing Non-Local Means filtering, images can effectively reduce noise while preserving important detail information, resulting in cleaner and smoother output images with maintained structural integrity.