Geometric transformation based independent component analysis for mixed image separation
| Autor: | Dien-Chi Wu, Che-Yen Wen, Chuan-Pin Lu, Shih-Hsuan Chiu |
|---|---|
| Rok vydání: | 2008 |
| Předmět: |
business.industry
Computer Science::Computer Vision and Pattern Recognition Image separation Scatter plot Geometric transformation General Engineering Normalization (image processing) Pattern recognition Artificial intelligence business Independent component analysis Geometric data analysis Mathematics |
| Zdroj: | Journal of the Chinese Institute of Engineers. 31:497-502 |
| ISSN: | 2158-7299 0253-3839 |
| DOI: | 10.1080/02533839.2008.9671403 |
| Popis: | An independent component analysis (ICA) method for image separation by geometric transformation of a scatter diagram is proposed. Geometric transformation and normalization are used to project mixed image signals to independent component space. This method includes four procedures: data correction, whitening, geometric rotation, and slant compensation. Several synthetic mixed image and real applications are used to evaluate the performance of the proposed method. From experimental results, mixed images are separated accurately by the proposed method. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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