Recursive order-statistic soft morphological filters

Document Type

Article

Publication Date

12-1-1997

Abstract

In this paper, a new class of the recursive order-statistic soft morphological (ROSSM) filters are proposed, and their important properties related to the morphological filtering are developed. Criteria for optimal selection of parameters are provided in order to achieve excellent performance in noise reduction and edge preservation. It is shown through experimental results that the ROSSM filters, compared with the order-statistic soft morphological filters or other well-known nonlinear filters, have a better outcome in signal reconstruction. Two examples are used for the extension of the proposed filters to illustrate their flexibilty. © 1997 IEEE.

Identifier

33747713957 (Scopus)

Publication Title

IEEE Transactions on Signal Processing

ISSN

1053587X

First Page

819

Issue

3

Volume

45

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