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

被引：9
|
作者：
Wang, ST [1 ]
Chung, FL
Li, YY
Hu, DW
Wu, XS
机构：
[1] Hong Kong Polytech Univ, Dept Comp, Hong Kong, Hong Kong, Peoples R China
[2] So Yangtze Univ, Sch Informat Engn, Wuxi, Peoples R China
[3] Natl Def Univ Sci & Technol, Sch Automat, Changsha, Peoples R China
来源：
SOFT COMPUTING | 2005年 / 9卷 / 05期
关键词：
image-processing; filter; Gaussian noise; type-2 fuzzy sets; fuzzy logic systems; neural networks;
D O I：
10.1007/s00500-004-0362-y
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
引用
收藏
页码：398 / 406
页数：9
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