DocumentCode
1524065
Title
Nonlinear filtering by threshold decomposition
Author
Lin, Jean-Hsang ; Ansari, Nirwan ; Li, Jinhui
Author_Institution
Comput. Commun. Lab., Ind. Technol. Res. Inst., Hsinchu, Taiwan
Volume
8
Issue
7
fYear
1999
fDate
7/1/1999 12:00:00 AM
Firstpage
925
Lastpage
933
Abstract
A new threshold decomposition architecture is introduced to implement stack filters. The architecture is also generalized to a new class of nonlinear filters known as threshold decomposition (TD) filters which are shown to be equivalent to the class of L1-filters under certain conditions. Another new class of filters known as linear and order statistic (LOS) filters result from the intersection of the class of TD and L1-filters. Performance comparisons among several filters are then presented. It was found that TD is compatible with L1, LOS, and linear filters in suppressing Gaussian noise, and is superior in suppressing salt-and-pepper noise. LOS filters, however, provide a better compromise in performance and complexity
Keywords
Gaussian noise; image processing; interference suppression; nonlinear filters; Gaussian noise suppression; L1-filters; LOS filters; TD filters; architecture; linear and order statistic filters; nonlinear filtering; salt-and-pepper noise; stack filters; threshold decomposition filters; AWGN; Additive noise; Additive white noise; Boolean functions; Computer architecture; Digital filters; Filtering; Finite impulse response filter; Gaussian noise; Nonlinear filters;
fLanguage
English
Journal_Title
Image Processing, IEEE Transactions on
Publisher
ieee
ISSN
1057-7149
Type
jour
DOI
10.1109/83.772235
Filename
772235
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