Prescanned minmax center-weighted filters for image restoration

Abstract

The prescanned minmax centre-weighted (PMCW) filter, which is capable of restoring images severely corrupted by impulsive noise, is presented. Before filtering, the input image is scanned by a running window; the maximum and minimum of each ranked set in the running window are grouped as the first subset, and the rest as the second subset. Then, the two subsets are filtered in sequence by a centered weight filter. It is shown that filtering results in the first subset provide the extension property by which the effective smoothing region for the subsequent filtering in the second subset is extended. The detail-control property of PMCW is characterised, and some relationships between PMCW and ranked-order based filters are derived. Quantitative comparisons demonstrate that the PMCW filter offers a more desirable combination of noise suppression and detail preservation properties than can other median-type filters.