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| Main Author: | |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2411.05265 |
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| _version_ | 1866913574273679360 |
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| author | Gilles, Jerome |
| author_facet | Gilles, Jerome |
| contents | This paper describes the many image decomposition models that allow to separate structures and textures or structures, textures, and noise. These models combined a total variation approach with different adapted functional spaces such as Besov or Contourlet spaces or a special oscillating function space based on the work of Yves Meyer. We propose a method to evaluate the performance of such algorithms to enhance understanding of the behavior of these models. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_05265 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Image Decomposition: Theory, Numerical Schemes, and Performance Evaluation Gilles, Jerome Image and Video Processing Computer Vision and Pattern Recognition Functional Analysis This paper describes the many image decomposition models that allow to separate structures and textures or structures, textures, and noise. These models combined a total variation approach with different adapted functional spaces such as Besov or Contourlet spaces or a special oscillating function space based on the work of Yves Meyer. We propose a method to evaluate the performance of such algorithms to enhance understanding of the behavior of these models. |
| title | Image Decomposition: Theory, Numerical Schemes, and Performance Evaluation |
| topic | Image and Video Processing Computer Vision and Pattern Recognition Functional Analysis |
| url | https://arxiv.org/abs/2411.05265 |