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A Tensor Regularized Nuclear Norm Method for Image and Video Completion.
- Source :
- Journal of Optimization Theory & Applications; Feb2022, Vol. 192 Issue 2, p401-425, 25p
- Publication Year :
- 2022
-
Abstract
- In the present paper, we propose two new methods for tensor completion of third-order tensors. The proposed methods consist in minimizing the average rank of the underlying tensor using its approximate function, namely the tensor nuclear norm. The recovered data will be obtained by combining the minimization process with the total variation regularization technique. We will adopt the alternating direction method of multipliers, using the tensor T-product, to solve the main optimization problems associated with the two proposed algorithms. In the last section, we present some numerical experiments and comparisons with the most known image video completion methods. [ABSTRACT FROM AUTHOR]
- Subjects :
- ALGORITHMS
VIDEOS
Subjects
Details
- Language :
- English
- ISSN :
- 00223239
- Volume :
- 192
- Issue :
- 2
- Database :
- Complementary Index
- Journal :
- Journal of Optimization Theory & Applications
- Publication Type :
- Academic Journal
- Accession number :
- 155153218
- Full Text :
- https://doi.org/10.1007/s10957-021-01947-3