DocumentCode
1467918
Title
Recursive order-statistic soft morphological filters
Author
Pei, S.-C. ; Lei, Chin-Laung ; Shih, F.Y.
Author_Institution
Dept. of Electr. Eng., Nat. Taiwan Univ., Taipei, Taiwan
Volume
145
Issue
5
fYear
1998
fDate
10/1/1998 12:00:00 AM
Firstpage
333
Lastpage
342
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 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
Keywords
filtering theory; mathematical morphology; nonlinear filters; recursive filters; signal reconstruction; statistical analysis; edge preservation; experimental results; morphological filtering; noise reduction; nonlinear filters; parameter selection; performance; recursive order-statistic soft morphological filters; signal processing applications; signal reconstruction;
fLanguage
English
Journal_Title
Vision, Image and Signal Processing, IEE Proceedings -
Publisher
iet
ISSN
1350-245X
Type
jour
DOI
10.1049/ip-vis:19982318
Filename
741946
Link To Document