MultiResolution Low-Rank Regularization of Dynamic Imaging Problems
Fuente:
arXiv
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| Autore principale: | |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Accesso online: | |
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| _version_ | 1866918113124024320 |
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| author | Heikkilä, Tommi |
| author_facet | Heikkilä, Tommi |
| contents | MultiResolution Low-Rank decomposition is formulated for regularization of dynamic image sequences. The decomposition applies a local low-rank decomposition on a sequence of discrete wavelet transforms. Its effective formulation as a regularization functional is discussed and numerically tested for dynamic X-ray tomography in comparison to other low-rank methods. The results suggest it is similar to traditional locally low-rank decomposition but produces less severe block artifacts. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_20977 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | MultiResolution Low-Rank Regularization of Dynamic Imaging Problems Heikkilä, Tommi Numerical Analysis 15A29, 65F55, 65T60, 65F22 MultiResolution Low-Rank decomposition is formulated for regularization of dynamic image sequences. The decomposition applies a local low-rank decomposition on a sequence of discrete wavelet transforms. Its effective formulation as a regularization functional is discussed and numerically tested for dynamic X-ray tomography in comparison to other low-rank methods. The results suggest it is similar to traditional locally low-rank decomposition but produces less severe block artifacts. |
| title | MultiResolution Low-Rank Regularization of Dynamic Imaging Problems |
| topic | Numerical Analysis 15A29, 65F55, 65T60, 65F22 |
| url | https://arxiv.org/abs/2502.20977 |