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 realparameter 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 reducingGaussian, impulse, and mixed-noise.
All Science Journal Classification (ASJC) codes
- Atomic and Molecular Physics, and Optics
- Computer Science Applications
- Electrical and Electronic Engineering