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| Natura: | Preprint |
| Pubblicazione: |
2024
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| Accesso online: | https://arxiv.org/abs/2411.00894 |
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| _version_ | 1866913570323693568 |
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| author | Gilles, Jerome |
| author_facet | Gilles, Jerome |
| contents | In this paper, we investigate theoretically the behavior of Meyer's image cartoon + texture decomposition model. Our main results is a new theorem which shows that, by combining the decomposition model and a well chosen Littlewood-Paley filter, it is possible to extract almost perfectly a certain class of textures. This theorem leads us to the construction of a parameterless multiscale texture separation algorithm. Finally, we propose to extend this algorithm into a directional multiscale texture separation algorithm by designing a directional Littlewood-Paley filter bank. Several experiments show the efficiency of the proposed method both on synthetic and real images. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_00894 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Multiscale texture separation Gilles, Jerome Image and Video Processing Computer Vision and Pattern Recognition Functional Analysis In this paper, we investigate theoretically the behavior of Meyer's image cartoon + texture decomposition model. Our main results is a new theorem which shows that, by combining the decomposition model and a well chosen Littlewood-Paley filter, it is possible to extract almost perfectly a certain class of textures. This theorem leads us to the construction of a parameterless multiscale texture separation algorithm. Finally, we propose to extend this algorithm into a directional multiscale texture separation algorithm by designing a directional Littlewood-Paley filter bank. Several experiments show the efficiency of the proposed method both on synthetic and real images. |
| title | Multiscale texture separation |
| topic | Image and Video Processing Computer Vision and Pattern Recognition Functional Analysis |
| url | https://arxiv.org/abs/2411.00894 |