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

Shu-Mei Guo; Chin-Chang Yang

doi:10.1117/1.3626843

1 July 2011 Fuzzy similarity measure-based hybrid image filter for color image restoration: multimethodology evolutionary computation

Shu-Mei Guo, Chin-Chang Yang

Author Affiliations +

Journal of Electronic Imaging, Vol. 20, Issue 3, 033015 (July 2011). https://doi.org/10.1117/1.3626843

Abstract

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) Society of Photo-Optical Instrumentation Engineers (SPIE)

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Shu-Mei Guo and Chin-Chang Yang "Fuzzy similarity measure-based hybrid image filter for color image restoration: multimethodology evolutionary computation," Journal of Electronic Imaging 20(3), 033015 (1 July 2011). https://doi.org/10.1117/1.3626843

Published: 1 July 2011

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