Presentation 2009-12-18
A proposed for the data-dependent Wiener filter
Mutsumi ONUMA, Satoru ISHII, Masaharu BABA, Hiroyuki TSUJI, Tomoaki KIMURA, Kazumasa AKIMOTO, Akira TAGUCHI,
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Abstract(in English) Wiener filter is generally used for restoring images polluted by optical blur and gaussian noise. Although Wiener filter estimates the power of Gaussian noise beforehand, a single time-invariant linear filter is used for restoring the entire image so the quality of restored images can be unsatisfactory. We propose the data-dependent Wiener filter that adaptively uses the appropriate filter coefficients at each pixels according to the two different information from the image domain. From the results of our experiments, the proposed method shows excellent results compared with the conventional Wiener filter.
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Keyword(in English) Wiener filter / Fuzzy reasoning / Gaussian noise / PSF(Point Spread Function)
Paper # SIS2009-43
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Committee SIS
Conference Date 2009/12/10(1days)
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Language JPN
Title (in Japanese) (See Japanese page)
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Title (in English) A proposed for the data-dependent Wiener filter
Sub Title (in English)
Keyword(1) Wiener filter
Keyword(2) Fuzzy reasoning
Keyword(3) Gaussian noise
Keyword(4) PSF(Point Spread Function)
1st Author's Name Mutsumi ONUMA
1st Author's Affiliation Faculty of information technology, Kanagawa Institute of Technology()
2nd Author's Name Satoru ISHII
2nd Author's Affiliation Faculty of information technology, Kanagawa Institute of Technology
3rd Author's Name Masaharu BABA
3rd Author's Affiliation Faculty of information technology, Kanagawa Institute of Technology
4th Author's Name Hiroyuki TSUJI
4th Author's Affiliation Faculty of information technology, Kanagawa Institute of Technology
5th Author's Name Tomoaki KIMURA
5th Author's Affiliation Faculty of information technology, Kanagawa Institute of Technology
6th Author's Name Kazumasa AKIMOTO
6th Author's Affiliation KYOCERA Corporation
7th Author's Name Akira TAGUCHI
7th Author's Affiliation Faculty of Engineering, Tokyo City University
Date 2009-12-18
Paper # SIS2009-43
Volume (vol) vol.109
Number (no) 338
Page pp.pp.-
#Pages 6
Date of Issue