Optimal order statistic filters with coefficient censoring

Abstract

Order statistic (OS) filters are noted for their robust properties for smoothing or estimating signals immersed in noise. The effect of coefficient censoring on the smoothing performance of OS filters is considered. Coefficient censoring can be effected either by adding zero coefficients to an existing filter, or by computing the optimal (MSE) censored coefficients for a set filter span. The second possibility is considered. In both cases, censoring can yield increased robustness and improved edge retention. OS filters in common use which can be interpreted as censored OS filters include the median filter, rank-order filters, and the trimmed mean filters. While optimal censored filters are generally suboptimal relative to optimal uncensored filters, they often yield superior performance for signals containing edge discontinuities. >