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

Authors:
S. T. Wangaff1n2;F. L. Chung;Y. Y. Li;D. W. Hu;X. S. Wu
Affiliations:
Department of Computing, Hong Kong Polytechnic University, Hong Kong and School of Information Engineering, Southern Yangtze University, Wuxi, China;Department of Computing, Hong Kong Polytechnic University, Hong Kong;School of Information Engineering, Southern Yangtze University, Wuxi, China;School of Automation, National Defense University of Science and Technology, ChangSha, China;School of Information Engineering, Southern Yangtze University, Wuxi, China
Venue:
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Year:
2005

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Cited 2

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Fuzzy Sets and Systems

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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.