Robust Edge Detection by Independent Component Analysis in Noisy Images(Image Processing and Video Processing)
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概要
- 論文の詳細を見る
We propose a robust edge detection method based on independent component analysis (ICA). It is known that most of the basis functions extracted from natural images by ICA are sparse and similar to localized and oriented receptive fields, and in the proposed edge detection method, a target image is first transformed by ICA basis functions and then the edges are detected or reconstructed with sparse components only. Furthermore, by applying a shrinkage algorithm to filter out the components of noise in the ICA domain, we can readily obtain the sparse components of the original image, resulting in a kind of robust edge detection even for a noisy image with a very low SN ratio. The efficiency of the proposed method is demonstrated by experiments with some natural images.
- 社団法人電子情報通信学会の論文
- 2004-09-01
著者
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Chen Yen-Wei
College of Information and Science, Ristumeikan University
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Han Xianhua
Graduate School Of Science And Engineering Ritsumeikan University
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Han Xian‐hua
Ritsumeikan Univ. Kusatsu‐shi Jpn
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Han Xian
Faculty Of Engineering University Of The Ryukyus
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Chen Y‐w
College Of Information Science And Engineering Ritsumeikan University
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Han Xian‐hua
College Of Information Science And Engineering Ritsumeikan University
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Chen Yen-wei
College Of Information And Science Ristumeikan University
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NAKAO Zensho
Faculty of Engineering, University of the Ryukyus
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HAN Xian-Hua
Faculty of Engineering, University of the Ryukyus
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Nakao Zensho
Faculty Of Engineering University Of The Ryukyus
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Han Xianhua
College of Information Science and Engineering, Ritsumeikan University
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