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
Recommended Citation
Pei, S. C.; Lai, C. L.; and Shih, F. Y., "Recursive order-statistic soft morphological filters" (1998). Faculty Publications. 16478.
https://digitalcommons.njit.edu/fac_pubs/16478
