Weighted myriad filters for image processing

Median filters, developed in response to the need for nonlinear image filters, have been used extensively in image processing. However, median filters do not work well when the outlier concentration is small, and are constrained to be smoothers, among other limitations. In order to combat the problems of median filters, weighted myriad filters have been proposed. Although myriad filters are analogous to both mean and median filters, myriad filters prove more effective in image processing applications. Weighted myriad filters have a sound theoretical basis, work well in impulsive noise environments, and can act as both edge enhancers and smoothers. This paper discusses optimization of the filter weights, with the goal of providing better image filtering than that of either linear or median filters