NDLI: Weighted fuzzy mean filters for heavy-tailed noise removal

Content Provider	IEEE Xplore Digital Library
Author	Chang-Shing Lee Yau-Hwang Kuo Pao-Ta Yu
Copyright Year	1995
Description	Author affiliation: Inst. of Inf. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan (Chang-Shing Lee; Yau-Hwang Kuo)
Abstract	A new fuzzy filter, called weighted fuzzy mean (WFM) filter is proposed and analyzed in this paper. The WFM filter is powerful for removing heavy additive impulse noises from images. By the filtering of each WFM filter, the filtered output signal is the mean value of the corrupted signals in a sample matrix, and these signals are weighted respectively by a membership grade of an associated fuzzy number stored in a knowledge base. The knowledge base contains a set of fuzzy numbers decided by experts or derived from the histogram of referred image. When the probability of occurrence of mixed impulse noises is over 0.3, the WFM filter can recover the noise-corrupted image quite well in contrast with the conventional filters, for examples, the median filters, nonlinear mean filters, RCRS, WOS, CWM, and stack filters, based on the mean absolute error (MAE) and mean square error (MSE) criteria. Besides, on the subjective evaluation of filtered images, the WFM filter results in a higher quality of global restoration.
Starting Page	601
Ending Page	606
File Size	649231
Page Count	6
File Format	PDF
ISBN	0818671262
DOI	10.1109/ISUMA.1995.527763
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1995-09-17
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Additive noise Image restoration Nonlinear filters Fuzzy set theory Image communication Information filtering Information filters Computer science Power engineering and energy Fuzzy sets
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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