Recursive order statistic soft morphological filters

A new class of recursive order-statistic soft morphological (ROSSM) filters are proposed and their important properties related to morphological filte ring are developed. Criteria for specific selection of parameters are provi ded to achieve excellent performance in noise reduction and edge preservati on. It is shown through experimental results that the ROSSM filters, compar ed to the order-statistic soft morphological filters or other well known no nlinear filters, have better outcomes in signal reconstruction. Two example s are given for demonstrating the flexibility of the proposed filters in si gnal processing applications.