A novel method of image filtering based on iterative fuzzy control

  • Authors:

  • Rui-hua Lu;Ming Yang;Yu-hui Qiu

  • Affiliations:

  • School of Electronic Information Engineering, Southwest China Normal University, Chongqing, China;School of Computer and Information Science, Southwest China Normal University, Chongqing, China;School of Computer and Information Science, Southwest China Normal University, Chongqing, China

  • Venue:
  • RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part II
  • Year:
  • 2005

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Abstract

A novel method of iterative fuzzy control-based filtering (IFCF) is proposed in this paper. The proposed method has outstanding characteristics of removing impulse noise and smoothing out Gaussian noise while preserving edges and image details effectively. This filtering approach is mainly based on the idea of not letting each point in the area of concern being uniformly fired by each of the basic fuzzy rules. The extended iterative fuzzy control-based filter (EIFCF) and the modified iterative fuzzy control-based filter (MIFCF) are presented in this paper too. EIFCF is mainly based on the idea that in each iteration the universe of discourse gets more shrunk and by shrinking the domains of the fuzzy linguistics, i.e., by compressing their membership function the number of fired fuzzy rules will be forced to keep unchanged in order to preserve the ability of the filter. MIFCF aims to enhance the property of the IFCF via increasing the iteration number without loosing edge information. Experiment results show that the proposed image filtering method based on iterative fuzzy control and its different modifications are very useful for image processing.