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Proceedings Paper

Adaptive L-filters based on fuzzy rules
Author(s): Akira Taguchi; Mitsuhiko Meguro
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Paper Abstract

An adaptive smoothing filter is proposed for reducing non-stationary or mixed noises efficiently. The output of the adaptive filter is the weighted sum of typical five L-filters' outputs. The weights are estimated by using fuzzy rules. Since the antecedents of the fuzzy rules can be composed of several local measurements, it is possible for the proposed filter to adjust its weights to adapt to local data. The performance of the proposed filter is compared to several reported filters.

Paper Details

Date Published: 28 March 1995
PDF: 9 pages
Proc. SPIE 2424, Nonlinear Image Processing VI, (28 March 1995); doi: 10.1117/12.205267
Show Author Affiliations
Akira Taguchi, Musashi Institute of Technology (Japan)
Mitsuhiko Meguro, Musashi Institute of Technology (Japan)


Published in SPIE Proceedings Vol. 2424:
Nonlinear Image Processing VI
Edward R. Dougherty; Jaakko T. Astola; Harold G. Longbotham; Nasser M. Nasrabadi; Aggelos K. Katsaggelos, Editor(s)

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