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.
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