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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2411.01788 |
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| _version_ | 1866929574772736000 |
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| author | Mao, Yu Gilles, Jerome |
| author_facet | Mao, Yu Gilles, Jerome |
| contents | A novel approach is presented to recover an image degraded by atmospheric turbulence. Given a sequence of frames affected by turbulence, we construct a variational model to characterize the static image. The optimization problem is solved by Bregman Iteration and the operator splitting method. Our algorithm is simple, efficient, and can be easily generalized for different scenarios. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_01788 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Non rigid geometric distortions correction -- Application to atmospheric turbulence stabilization Mao, Yu Gilles, Jerome Computer Vision and Pattern Recognition A novel approach is presented to recover an image degraded by atmospheric turbulence. Given a sequence of frames affected by turbulence, we construct a variational model to characterize the static image. The optimization problem is solved by Bregman Iteration and the operator splitting method. Our algorithm is simple, efficient, and can be easily generalized for different scenarios. |
| title | Non rigid geometric distortions correction -- Application to atmospheric turbulence stabilization |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2411.01788 |