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

Shu Mei Guo, Chin Chang Yang

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

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 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.

Original languageEnglish
Article number033015
JournalJournal of Electronic Imaging
Volume20
Issue number3
DOIs
Publication statusPublished - 2011 Jul

All Science Journal Classification (ASJC) codes

  • Atomic and Molecular Physics, and Optics
  • Computer Science Applications
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'Fuzzy similarity measure-based hybrid image filter for color image restoration: Multimethodology evolutionary computation'. Together they form a unique fingerprint.

Cite this