1 July 2011 Fuzzy similarity measure-based hybrid image filter for color image restoration: multimethodology evolutionary computation
Author Affiliations +
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, Shu-Mei Guo, Chin-Chang Yang, 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:
JOURNAL ARTICLE
19 PAGES


SHARE
RELATED CONTENT

Fuzzy filters for image smoothing
Proceedings of SPIE (April 30 1994)
Analysis of the sigma filter using robust estimation
Proceedings of SPIE (February 28 2005)
Adaptive neighborhood filters for color image filtering
Proceedings of SPIE (April 05 1998)

Back to Top