Presentation 2004/3/8
An Improvement of An Adaptive Weighted Mean Filter Using Fuzzy Clustering and Its Improvement
Takehiro IMAI, Tetsuya ODA, Mitsuji MUNEYASU, Takao HINAMOTO,
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Abstract(in English) This paper proposes a novel edge-preserving adaptive weighted mean filter using fuzzy clustering and its improvement. The proposing filter firstly calculates the weighted means of inputs by the weights which have been already adjusted for each cluster centroids. The filter output is the weighted mean of them, by the weights which are membership grades of the input for each cluster. The proposing filter can finely remove mixed noise with preserving edges, because a fuzzy clustering can flexibly classify ambiguous local image information and can adaptively control filter weights. Finally, simulation examples show the effectiveness of the proposed technique.
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Keyword(in English) data-dependent filter / weighted mean filter / noise reduction / fuzzy clustering
Paper # CAS2003-110,DSP2003-212,CS2003-162
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Committee CS
Conference Date 2004/3/8(1days)
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Registration To Communication Systems (CS)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) An Improvement of An Adaptive Weighted Mean Filter Using Fuzzy Clustering and Its Improvement
Sub Title (in English)
Keyword(1) data-dependent filter
Keyword(2) weighted mean filter
Keyword(3) noise reduction
Keyword(4) fuzzy clustering
1st Author's Name Takehiro IMAI
1st Author's Affiliation Graduate School of Engineering, Kansai University()
2nd Author's Name Tetsuya ODA
2nd Author's Affiliation Graduate School of Engineering, Hiroshima University
3rd Author's Name Mitsuji MUNEYASU
3rd Author's Affiliation Graduate School of Engineering, Kansai University
4th Author's Name Takao HINAMOTO
4th Author's Affiliation Graduate School of Engineering, Hiroshima University
Date 2004/3/8
Paper # CAS2003-110,DSP2003-212,CS2003-162
Volume (vol) vol.103
Number (no) 720
Page pp.pp.-
#Pages 6
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