An Unsupervised Optimization of Structuring Elements for Noise Removal Using GA
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概要
- 論文の詳細を見る
In this paper we propose an unsupervised method of optimizing structuring elements (SEs) used for impulse noise reduction in texture images through the opening operation which is one of the morphological operations. In this method, a genetic algorithm (GA), which can effectively search wide search spaces, is applied and the size of the shape of the SE is included in the design variables. Through experiments, it is shown that our new approach generally outperforms the conventional method.
- （社）電子情報通信学会の論文
- 2010-11-01
著者
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ASANO Akira
Graduate School of Engineering, Hiroshima University
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Muneyasu Mitsuji
Kansai Univ. Suita‐shi Jpn
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Muneyasu Mitsuji
Faculty Of Engineering Frontier Science Center Kansai University
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Asano Akira
Hiroshima Univ. Hiroshima Jpn
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Asano Akira
Graduate School Of Engineering Hiroshima University
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OKUNO Hiroyuki
Faculty of Engineering Science, Kansai University
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HANADA Yoshiko
Faculty of Engineering Science, Kansai University
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Hanada Yoshiko
Faculty Of Engineering Science Kansai University
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Okuno Hiroyuki
Faculty Of Engineering Science Kansai University
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MUNEYASU Mitsuji
Faculty of Engineering and Science, Kansai University
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- FOREWORD
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