Presentation 2009-09-25
Extension of Unsupervised Design Method for Weighted Median Filters Using GA
Yoshiko HANADA, Mitsuji MUNEYASU, Akira ASANO,
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Abstract(in English) Estimation of a suitable window shape and appropriate weights in weighted median filters is one of important problems. In this study, we formulate the design of weighted median filter as an optimization problem, and optimal window shapes and weights are estimated directly from degraded images. In the previous work, we estimated them by using a Genetic Algorithm (GA) on texture images corrupted by positive impulse noises. Here, we extends our proposed unsupervised design to the positive and negative impulse removal. Through experiments, it is shown that designed filters outperform compared to conventional impulse noise filters from the perspective of both high noise removal performance and preservative quality.
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Keyword(in English) texture images / impulse noise / weighted median filter / genetic algorithm
Paper # SIP2009-49,SIS2009-24
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Committee SIS
Conference Date 2009/9/17(1days)
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Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Extension of Unsupervised Design Method for Weighted Median Filters Using GA
Sub Title (in English)
Keyword(1) texture images
Keyword(2) impulse noise
Keyword(3) weighted median filter
Keyword(4) genetic algorithm
1st Author's Name Yoshiko HANADA
1st Author's Affiliation Faculty of Engineering Science, Kansai University()
2nd Author's Name Mitsuji MUNEYASU
2nd Author's Affiliation Faculty of Engineering Science, Kansai University
3rd Author's Name Akira ASANO
3rd Author's Affiliation Graduate School of Engineering, Hiroshima University
Date 2009-09-25
Paper # SIP2009-49,SIS2009-24
Volume (vol) vol.109
Number (no) 203
Page pp.pp.-
#Pages 6
Date of Issue