Hyperspectral Image Restoration via Auto-Weighted Nonlocal Tensor Ring Rank Minimization
Author:
Affiliation:
1. School of Mathematics and Computer Science, Panzhihua University, Panzhihua, China
2. College of Computer Science, China West Normal University, Nanchong, China
Funder
Science and Technology Support Project, Panzhihua, Sichuan, China
Innovation Team Funds of China West Normal University
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Geotechnical Engineering and Engineering Geology
Link
http://xplorestaging.ieee.org/ielx7/8859/9651998/09861639.pdf?arnumber=9861639
Reference20 articles.
1. Elastic Reflection Waveform Inversion with a Nonlinear Born Scattering Operator for Multi-parameter Reconstruction
2. Tensor-ring Nuclear Norm Minimization and Application for Visual : Data Completion
3. Tensor completion via nonconvex tensor ring rank minimization with guaranteed convergence
4. Auto-weighted robust low-rank tensor completion via tensor-train
5. Hyperspectral Mixed Noise Removal By $\ell _1$-Norm-Based Subspace Representation
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1. Hyperspectral image restoration via hybrid smoothness regularized auto-weighted low-rank tensor ring factorization;Frontiers in Earth Science;2023-01-05
2. Integrated Spatio-Spectral–Temporal Fusion via Anisotropic Sparsity Constrained Low-Rank Tensor Approximation;IEEE Transactions on Geoscience and Remote Sensing;2023
3. FuBay: An Integrated Fusion Framework for Hyperspectral Super-Resolution Based on Bayesian Tensor Ring;IEEE Transactions on Neural Networks and Learning Systems;2023
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