Learnable Spatial-Spectral Transform-Based Tensor Nuclear Norm for Multi-Dimensional Visual Data Recovery

Recently, transform-based tensor nuclear norm (TNN) methods have received increasing attention as a powerful tool for multi-dimensional visual data (color images, videos, and multispectral images, etc.) recovery. Especially, the redundant transform-based TNN achieves satisfactory recovery results, w...

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Vydané v:	IEEE transactions on circuits and systems for video technology Ročník 34; číslo 5; s. 3633 - 3646
Hlavní autori:	Liu, Sheng, Leng, Jinsong, Zhao, Xi-Le, Zeng, Haijin, Wang, Yao, Yang, Jing-Hua
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.05.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Algorithms Color imagery Computational efficiency Costs Data recovery Decoding Encoding Multidimensional methods proximal alternating minimization algorithm Redundancy redundant transform semi-orthogonal transform Tensor completion tensor nuclear norm Tensors Transforms Video Videos Visualization
ISSN:	1051-8215, 1558-2205
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