Novel detail-preserving robust filter for multiplicative and additive noise suppression in image processing

Abstract

In this paper, we present a robust image filter that provides preservation of fine details and effective suppression of intensive multiplicative noise. The filter is based on the use of 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 image filters uses the central pixel of the filtering window and the redescending M-estimators combined with the median estimator. At the second stage, to provide multiplicative noise suppression, a modified Sigma filter that implements the calculation scheme of a redescending M-estimator, is used. Visual and analytical analysis of simulation results shows that the proposed image filter has demonstrated fine detail preservation, good multiplicative noise suppression and impulsive noise removal.