Presentation 2008-12-05
An Unsupervised Optimization of Structuring Elements for Image Denoising Using GA
Hiroyuki OKUNO, Yoshiko HANADA, Mitsuji MUNEYASU, Akira ASANO,
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Abstract(in English) To recover texture images from impulse noise by the opening operation which is one of morphological operations, an suitable structure element (SE) has to be estimated. Hitherto, an unsupervised design method for the SEs has been proposed, and it have adopted Simulated Annealing (SA) as an optimization method. In this approach, SEs are designed under a neighborhood structure which keeps the size of shape, and the size is gradually reduced in the search process. Due to this, the search space is restricted. In this paper, Genetic Algorithm (GA) which can search effectively on wide search spaces is applied. Through experiments, it is shown that our new approach outperformes conventional methods.
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Keyword(in English) texture images / impulse noise / structuring element / genetic algorithm / morphology
Paper # SIS2008-65
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Committee SIS
Conference Date 2008/11/27(1days)
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Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) An Unsupervised Optimization of Structuring Elements for Image Denoising Using GA
Sub Title (in English)
Keyword(1) texture images
Keyword(2) impulse noise
Keyword(3) structuring element
Keyword(4) genetic algorithm
Keyword(5) morphology
1st Author's Name Hiroyuki OKUNO
1st Author's Affiliation Faculty of Engineering Science, Kansai University()
2nd Author's Name Yoshiko HANADA
2nd Author's Affiliation Faculty of Engineering Science, Kansai University
3rd Author's Name Mitsuji MUNEYASU
3rd Author's Affiliation Faculty of Engineering Science, Kansai University
4th Author's Name Akira ASANO
4th Author's Affiliation Graduate School of Engineering, Hiroshima University
Date 2008-12-05
Paper # SIS2008-65
Volume (vol) vol.108
Number (no) 334
Page pp.pp.-
#Pages 6
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