Recursive order-statistic soft morphological filters

Document Type

Article

Publication Date

1-1-1998

Abstract

A new class of recursive order-statistic soft morphological (ROSSM) filters are proposed and their important properties related to morphological filtering are developed. Criteria for specific selection of parameters are provided to achieve excellent performance in noise reduction and edge preservation. It is shown through experimental results that the ROSSM filters, compared to the order-statistic soft morphological filters or other well known nonlinear filters, have better outcomes in signal reconstruction. Two examples are given for demonstrating the flexibility of the proposed filters in signal processing applications. © IEE, 1998.

Identifier

0032184496 (Scopus)

Publication Title

IEE Proceedings Vision Image and Signal Processing

External Full Text Location

https://doi.org/10.1049/ip-vis:19982318

ISSN

1350245X

First Page

333

Last Page

340

Issue

5

Volume

145

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