An improved recursive median filtering scheme for image processing
In a recent publication, it was shown that median filtering is an optimization process in which a two-term cost function is minimized. Based on this functional optimization property of the median filtering process, a new approach for designing the recursive median filter for image processing applications is introduced in this paper. We prove that the new approach is guaranteed to converge to root within a finite number of iterations. The new method is applied to process a real image corrupted by pseudorandom impulsive noise, and the results show that the new scheme provides improved mean square error (RISE) performance over the standard recursive median filters.