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ASME Press Select Proceedings
Intelligent Engineering Systems through Artificial Neural Networks, Volume 16
ISBN-10:
0791802566
No. of Pages:
1000
Publisher:
ASME Press
Publication date:
2006
eBook Chapter
71 A Novel Approach to Reduce Universal Noise in Gray Images Using Fuzzy Filters
By
M. Hanmandlu
,
M. Hanmandlu
Dept. of Electrical Engg.,
IIT Delhi
, New Delhi-110 016
, India
.
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Anuj K. Tiwari
,
Anuj K. Tiwari
Dept. of Electrical Engg.,
IIT Delhi
, New Delhi-110 016
, India
.
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Vamsi K. Madasu
,
Vamsi K. Madasu
School of Engg. Systems,
Queensland Univ. of Tech.
, Brisbane
, Australia
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Shantaram Vasikarla
Shantaram Vasikarla
American InterCont. Univ.
12655 W. Jefferson Blvd. Los Angeles, CA 90066
USA
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Page Count:
6
-
Published:2006
Citation
Hanmandlu, M, Tiwari, AK, Madasu, VK, & Vasikarla, S. "A Novel Approach to Reduce Universal Noise in Gray Images Using Fuzzy Filters." Intelligent Engineering Systems through Artificial Neural Networks, Volume 16. Ed. Dagli, CH, Buczak, AL, Enke, DL, Embrechts, M, & Ersoy, O. ASME Press, 2006.
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This paper presents the fuzzy filter consisting of the two filters, Gaussian and Impulse noise filters for eliminating the mixed noise. For Gaussian filter, the fuzzy set called “small” is derived to represent the disorder in a pixel arising out of neighborhood corrupted with Gaussian. Next, expression for correction is developed based on the intensity of the central pixel and the membership function. Similarly, the correction for the Impulse noise is developed by finding the middle ranking pixels in the neighborhood of the central pixel. The difference between the average of the middle ranking pixels and the central pixels is...
Abstract
1. Introduction
3. Fuzzy filter for Impulse noise Correction
4. Combined Fuzzy Filter for Mixed Noise Removal
5. Results
6. Conclusions
References
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