Robust Low Transformed Multi-Rank Tensor Completion With Deep Prior Regularization for Multi-Dimensional Image Recovery-Reference-Cited by-同舟云学术

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Robust Low Transformed Multi-Rank Tensor Completion With Deep Prior Regularization for Multi-Dimensional Image Recovery

Published:2023-10 Issue:5 Volume:9 Page:1288-1301
ISSN:2332-7790
Container-title:IEEE Transactions on Big Data
language:
Short-container-title:IEEE Trans. Big Data

Author:

Li Yao¹^ORCID,Qiu Duo²^ORCID,Zhang Xiongjun³^ORCID

Affiliation:

1. School of Future Technology, China University of Geoscience, Wuhan, China

2. School of Mathematics and Physics, Wuhan Institute of Technology, Wuhan, China

3. School of Mathematics and Statistics, and Hubei Key Laboratory of Mathematical Sciences, Central China Normal University, Wuhan, China

Funder

National Natural Science Foundation of China

Science Foundation of Wuhan Institute of Technology

Knowledge Innovation Project of Wuhan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Information Systems and Management,Information Systems

Link

http://xplorestaging.ieee.org/ielx7/6687317/10236926/10064022.pdf?arnumber=10064022

Reference74 articles.

1. Factorization strategies for third-order tensors

2. Double-Factor-Regularized Low-Rank Tensor Factorization for Mixed Noise Removal in Hyperspectral Image

3. Tensor-Train Decomposition

4. Total-Variation-Regularized Low-Rank Matrix Factorization for Hyperspectral Image Restoration

5. Most Tensor Problems Are NP-Hard

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Low-rank tensor completion via nonlocal self-similarity regularization and orthogonal transformed tensor Schatten-p norm;Pattern Analysis and Applications;2024-07-22

2. 1-Bit Tensor Completion via Max-and-Nuclear-Norm Composite Optimization;IEEE Transactions on Signal Processing;2024

3. Multi-Dimensional Data Recovery via Feature-Based Fully-Connected Tensor Network Decomposition;IEEE Transactions on Big Data;2023

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