Complex-fuzzy adaptive image restoration - An artificial-bee-colony-based learning approach

Chunshien Li, Fengtse Chan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

19 Scopus citations

Abstract

A complex-fuzzy approach using complex fuzzy sets is proposed in the paper to deal with the problem of adaptive image noise cancelling. A image may be corrupted by noise, resulting in the degradation of valuable image information. Complex fuzzy set (CFS) is in contrast with traditional fuzzy set in membership description. A CFS has the membership state within the complexvalued unit disc of the complex plane. Based on the membership property of CFS, we design a complex neural fuzzy system (CNFS), so that the functional mapping ability by the CNFS can be augmented. A hybrid learning method is devised for training of the proposed CNFS, including the artificial bee colony (ABC) method and the recursive least square estimator (RLSE) algorithm. Two cases for image restoration are used to test the proposed approach. Experimental results are shown with good restoration quality.

Original languageEnglish
Title of host publicationIntelligent Information and Database Systems - Third International Conference, ACIIDS 2011, Proceedings
Pages90-99
Number of pages10
EditionPART 2
DOIs
StatePublished - 2011
Event3rd International Conference on Intelligent Information and Database Systems, ACIIDS 2011 - Daegu, Korea, Republic of
Duration: 20 Apr 201122 Apr 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume6592 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd International Conference on Intelligent Information and Database Systems, ACIIDS 2011
Country/TerritoryKorea, Republic of
CityDaegu
Period20/04/1122/04/11

Keywords

  • Artificial bee colony (ABC)
  • Complex fuzzy set (CFS)
  • Complex neuro-fuzzy system (CNFS)
  • Image restoration
  • Recursive least square estimator (RLSE)

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