Novel detail-preserving robust RM-KNN filters with impulsive noise suppression for image processing

We introduce novel robust filtering algorithms applicable to image processing. They were derived using RM-type point estimations and the restriction technique of the well-known specific for image processing KNN filter. The derived RM-KNN filters effectively remove impulsive noise while edge and fine details are preserved. The proposed filters were tested on simulated images and real data and were provided excellent visual quality of the processed images and good quantitative quality in the MSE sense over standard median filter. Recommendations to obtain best processing results by proper selection of derived filter parameters are given. Two derived filters are suitable for impulsive noise reduction in any image processing applications. One can use the RM-KNN filters as the first stage of image enhancement following by any non-robust techniques such as Sigma-filter on the second stage.