Using an adaptive neuro-fuzzy inference system-based interpolant for impulsive noise suppression from highly distorted images

Besdok E., Civicioglu P., Alci M.

FUZZY SETS AND SYSTEMS, vol.150, no.3, pp.525-543, 2005 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 150 Issue: 3
  • Publication Date: 2005
  • Doi Number: 10.1016/j.fss.2004.06.018
  • Journal Name: FUZZY SETS AND SYSTEMS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.525-543
  • Keywords: impulsive noise, Chi-square goodness-of-fit test, DSF interpolant, ANFIS, MEDIAN FILTERS, TAKAGI-SUGENO, REMOVAL, MODELS
  • Erciyes University Affiliated: Yes

Abstract

A new impulsive noise (IN) suppression filter, entitled Adaptive neuro-fuzzy inference system (ANFIS)-based impulsive noise suppression Filter, which shows a high performance at the restoration of images distorted by IN, is proposed in this paper. The extensive simulation results show that the proposed filter achieves a superior performance to the other filters mentioned in this paper in the cases of being effective in noise suppression and detail preservation, especially when the noise density is very high. (C) 2004 Elsevier B.V. All rights reserved.