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Fuzzy similarity measure-based hybrid image filter for color image restoration: multimethodology evolutionary computation

[+] Author Affiliations
Shu-Mei Guo

National Cheng-Kung University, Department of Computer and Information Engineering, Tainan 701, Taiwan

Chin-Chang Yang

National Cheng-Kung University, Department of Computer and Information Engineering, Tainan 701, Taiwan

J. Electron. Imaging. 20(3), 033015 (September 12, 2011). doi:10.1117/1.3626843
History: Received April 26, 2010; Revised June 18, 2011; Accepted July 28, 2011; Published September 12, 2011; Online September 12, 2011
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A fuzzy similarity measure-based hybrid image filter (FHF) is proposed for color image restoration in this paper. Operation is carried out in three steps: parameter optimization, hybrid image filter setup, and image restoration. For parameter optimization, a multimethodology evolutionary computation (MMEC) is presented for real-parameter optimization problems. Then, FHF with a fuzzy-based similarity measure is introduced for noise reduction. Finally, a color image is restored with an experience-based construction of FHF which has been optimized via MMEC. Experimental results show the proposed FHF achieves a high peak signal-to-noise ratio and mean structural similarity by effectively reducing Gaussian, impulse, and mixed-noise.

© 2011 SPIE and IS&T

Citation

Shu-Mei Guo and Chin-Chang Yang
"Fuzzy similarity measure-based hybrid image filter for color image restoration: multimethodology evolutionary computation", J. Electron. Imaging. 20(3), 033015 (September 12, 2011). ; http://dx.doi.org/10.1117/1.3626843


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