A new gaussian noise filter based on interval type-2 fuzzy logic systems

S. T. Wang, Fu Lai Korris Chung, Y. Y. Li, D. W. Hu, X. S. Wu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

14 Citations (Scopus)

Abstract

In this paper, a new selective feedback fuzzy neural network (SFNN) based on interval type-2 fuzzy logic systems is introduced by partitioning input and output spaces and based upon which a new FLS filter is further studied. The experimental results demonstrate that this new FLS filter outperforms other filters (e.g. the mean filter and the Wiener filter) in suppressing Gaussian noise and maintaining the original structure of an image.
Original languageEnglish
Pages (from-to)398-406
Number of pages9
JournalSoft Computing
Volume9
Issue number5
DOIs
Publication statusPublished - 1 May 2005

Keywords

  • Filter
  • Fuzzy logic systems
  • Gaussian noise
  • Image-processing
  • Neural networks
  • Type-2 fuzzy sets

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Geometry and Topology

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