Presentation 2012-03-01
Improvement of Unsupervised Design Method of Weighted Median Filters Using Genetic Algorithm
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 estimate optimal filters directly from degraded images. In our previous work, we estimated optimal window shapes and weights by using a Genetic Algorithm (GA) with a fixed size of window as a constraint in optimization. To determine an appropriate window size is difficult but essential since it depends on both a type of texture and a noise rate. Here, we optimize weighted median niters without the constraint in the size of filters. Numerical experiments show that designed filters outperform the niters obtained by our previous approach.
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Keyword(in English) texture images / impulse noise / weighted median filter / genetic algorithm
Paper # SIS2011-62
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Committee SIS
Conference Date 2012/2/23(1days)
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Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Improvement of Unsupervised Design Method of Weighted Median Filters Using Genetic Algorithm
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 Faculty of Informatics, Kansai University
Date 2012-03-01
Paper # SIS2011-62
Volume (vol) vol.111
Number (no) 457
Page pp.pp.-
#Pages 6
Date of Issue