Detection of moving objects through turbulent media. Decomposition of Oscillatory vs Non-Oscillatory spatio-temporal vector fields
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arXiv
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| Autores principales: | , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866916457318711296 |
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| author | Gilles, Jerome Alvarez, Francis Ferrante, Nicholas B. Fortman, Margaret Tahir, Lena Tarter, Alex von Seeger, Anneke |
| author_facet | Gilles, Jerome Alvarez, Francis Ferrante, Nicholas B. Fortman, Margaret Tahir, Lena Tarter, Alex von Seeger, Anneke |
| contents | In this paper, we investigate how moving objects can be detected when images are impacted by atmospheric turbulence. We present a geometric spatio-temporal point of view to the problem and show that it is possible to distinguish movement due to the turbulence vs. moving objects. To perform this task, we propose an extension of 2D cartoon+texture decomposition algorithms to 3D vector fields. Our algorithm is based on curvelet spaces which permit to better characterize the movement flow geometry. We present experiments on real data which illustrate the efficiency of the proposed method. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_21551 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Detection of moving objects through turbulent media. Decomposition of Oscillatory vs Non-Oscillatory spatio-temporal vector fields Gilles, Jerome Alvarez, Francis Ferrante, Nicholas B. Fortman, Margaret Tahir, Lena Tarter, Alex von Seeger, Anneke Computer Vision and Pattern Recognition In this paper, we investigate how moving objects can be detected when images are impacted by atmospheric turbulence. We present a geometric spatio-temporal point of view to the problem and show that it is possible to distinguish movement due to the turbulence vs. moving objects. To perform this task, we propose an extension of 2D cartoon+texture decomposition algorithms to 3D vector fields. Our algorithm is based on curvelet spaces which permit to better characterize the movement flow geometry. We present experiments on real data which illustrate the efficiency of the proposed method. |
| title | Detection of moving objects through turbulent media. Decomposition of Oscillatory vs Non-Oscillatory spatio-temporal vector fields |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2410.21551 |