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Journal of Electronic Imaging

On the design of neuro-fuzzy hybrid multichannel filters to remove impulsive noise for color image restoration
Author(s): HungHsu Tsai; ShenHwang Chen; PaoTa Yu
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Paper Abstract

This paper proposes a novel class of multichannel filters called neuro-fuzzy hybrid multichannel (NFHM) filters to simultaneously achieve three objectives: noise attenuation, chromaticity retention, and edges or details preservation. NFHM filters are characterized by a set of fuzzy rules (structure knowledge) such that they are capable of effectively fusing together the useful filtering merits from vector median, vector directional, and identity filters to further improve the filtering performance of the conventional filters. Moreover, we adequately exploit the functional equivalence between fuzzy inference systems and radial-basis function networks on the optimal design of NFHM filters such that NFHM filters can be optimized by neuro-learning techniques based on the radial-basis function networks to obtain adaptive fuzzy rules for the different window contents. Finally, extensive simulation results demonstrate that the filtering performance of NFHM filters is superior to that of other proposed filters.

Paper Details

Date Published: 1 April 2000
PDF: 23 pages
J. Electron. Imag. 9(2) doi: 10.1117/1.482733
Published in: Journal of Electronic Imaging Volume 9, Issue 2
Show Author Affiliations
HungHsu Tsai, National Chung Cheng Univ. (Taiwan)
ShenHwang Chen, National Chung Cheng Univ. (Taiwan)
PaoTa Yu, National Chung Cheng Univ. (Taiwan)


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