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MultiResolution Low-Rank Regularization of Dynamic Imaging Problems

Numerical Analysis 2025-08-05 v1 Numerical Analysis

Abstract

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.

Keywords

Cite

@article{arxiv.2502.20977,
  title  = {MultiResolution Low-Rank Regularization of Dynamic Imaging Problems},
  author = {Tommi Heikkilä},
  journal= {arXiv preprint arXiv:2502.20977},
  year   = {2025}
}

Comments

13 pages, 5 figures, SSVM 2025 conference

R2 v1 2026-06-28T22:01:43.128Z