Fuzzy filters for noise reduction: The case of Gaussian noise

被引：0
|
作者：
Nachtegael, M [1 ]
Schulte, S [1 ]
Van der Weken, D [1 ]
De Witte, V [1 ]
Kerre, EE [1 ]
机构：
[1] Univ Ghent, Dept Appl Math & Comp Sci, B-9000 Ghent, Belgium
来源：
FUZZ-IEEE 2005: PROCEEDINGS OF THE IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS: BIGGEST LITTLE CONFERENCE IN THE WORLD | 2005年
关键词：
image processing; noise reduction; fuzzy filters; gaussian noise;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Noise reduction is a well-known problem in image processing. The reduction of noise in an image sometimes is as a goal itself, and sometimes is considered as a pre-processing step. Besides the classical filters for noise reduction, quite a lot of fuzzy inspired filters have been proposed during the past years. However, it is very difficult to judge the quality of this wide variety of filters. For which noise types are they designed? How do they perform for those noise types? How do they perform compared to each other? Can we select filters that clearly outperform the others? Is there a difference between numerical and visual results? In this paper, we answer these questions for images that are corrupted with gaussian noise.
引用
收藏
页码：201 / 206
页数：6
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