Robust rank detail-preserving filters with noise suppression in image processing applications

In this paper, we present a robust image filtering algorithms that provide preservation of fine details and strong speckle noise suppression. They were derived using our approach for robust filter design. According to this approach, we used M (robust maximum likelihood)-estimators and R(rank)-estimators derived from the statistical theory of rank tests. At the first stage, to provide impulsive noise rejection, the introduced robust image filters use the central pixel of the filtering window and the redescending M-estimators combined with the median or Wilcoxon estimators. At the second stage, to provide multiplicative noise suppression, a modified Sigma filter that implements the iterative calculation scheme of a redescending M-estimator, is used. The proposed robust rank detail-preserving filter demonstrated excellent fine detail preservation and impulsive noise removal. Visual and analytical analysis of these results shows the algorithms proposed on the base of RM approach provide good visual quality of processed data and possess good speckle noise attenuation capabilities.