| Presentation | 2011-07-26 An image decomposition method by translation-invariant dictionary learning with TV regularization and its application to image inpainting Makoto NAKASHIZUKA, |
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| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In this paper, an image decomposition that represents an image as a sum of a cartoon component and texture components is proposed. TV minimization methods have been applied to the image decomposition into two components, the cartoon and the texture. We introduce the translation invariant dictionary learning with sparsity prior into the texture decomposition. The generating atoms, each of which represents a micro structure of a texture component, are learnt from the image. The texture component is decomposed into the different components with the learnt generating atoms. In experiments, the proposed image model is applied to the image inpainting, and compared with the inpainting method with a wavelet dictionary under sparsity prior. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Image decomposition / sparse signal representation / dictionary learning / total variation / image inparinting |
| Paper # | IE2011-45 |
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| Conference Information | |
| Committee | IE |
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| Conference Date | 2011/7/18(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
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| Paper Information | |
| Registration To | Image Engineering (IE) |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | An image decomposition method by translation-invariant dictionary learning with TV regularization and its application to image inpainting |
| Sub Title (in English) | |
| Keyword(1) | Image decomposition |
| Keyword(2) | sparse signal representation |
| Keyword(3) | dictionary learning |
| Keyword(4) | total variation |
| Keyword(5) | image inparinting |
| 1st Author's Name | Makoto NAKASHIZUKA |
| 1st Author's Affiliation | Graduate School of Engineering Science, Osaka University() |
| Date | 2011-07-26 |
| Paper # | IE2011-45 |
| Volume (vol) | vol.111 |
| Number (no) | 156 |
| Page | pp.pp.- |
| #Pages | 5 |
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