Recursive order-statistic soft morphological filters
Journal
IEE Proceedings: Vision, Image and Signal Processing
Journal Volume
145
Journal Issue
5
Pages
333-340
Date Issued
1998-10
Date
1998-10
Author(s)
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.
Subjects
Image reconstruction; Morphological filtering; Recursive order-statistic soft morphological filters
Other Subjects
Edge detection; Noise abatement; Parameter estimation; Performance; Recursive functions; Signal filtering and prediction; Statistical methods; Morphological filtering; Image reconstruction
Type
journal article
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