Nonlinear hierarchical matrix factorization-based tensor ring approximation for multi-dimensional image recovery
DOI10.1007/s10915-024-02670-7zbMATH Open1547.65049MaRDI QIDQ6629208
Hao Zhang, Xi-Le Zhao, Zhi-Long Han, Wei-Hao Wu, Ting-Zhu Huang
Publication date: 29 October 2024
Published in: Journal of Scientific Computing (Search for Journal in Brave)
multi-dimensional image recoverynonlinear hierarchical matrix factorizationtensor ring approximationtheoretical error bound
Factorization of matrices (15A23) Numerical mathematical programming methods (65K05) Computing methodologies for image processing (68U10) Numerical aspects of computer graphics, image analysis, and computational geometry (65D18) Multilinear algebra, tensor calculus (15A69) Numerical linear algebra (65F99)
Cites Work
- Tensor-Train Decomposition
- Parallel matrix factorization for low-rank tensor completion
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- Probability inequalities for the sum in sampling without replacement
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- Multiplicative algorithms for symmetric nonnegative tensor factorizations and its applications
- Robust Low-Rank Tensor Recovery: Models and Algorithms
- Efficient Tensor Completion for Color Image and Video Recovery: Low-Rank Tensor Train
- Robust Tensor Completion: Equivalent Surrogates, Error Bounds, and Algorithms
- Practical sketching algorithms for low-rank Tucker approximation of large tensors
- Enhanced Low-Rank Tensor Recovery Fusing Reweighted Tensor Correlated Total Variation Regularization for Image Denoising
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