1 July 2011 Fuzzy similarity measure-based hybrid image filter for color image restoration: multimethodology evolutionary computation
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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)
Shu-Mei Guo, 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 . Submission:
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