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Nonlocal Low-Rank Regularized Tensor Decomposition for Hyperspectral Image Denoising

IEEE transactions on geoscience and remote sensing, 2019-07, Vol.57 (7), p.5174-5189

2019

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Spatial-Spectral Structured Sparse Low-Rank Representation for Hyperspectral Image Super-Resolution

IEEE transactions on image processing, 2021, Vol.30, p.3084-3097

2021

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Joint Spatial and Spectral Low-Rank Regularization for Hyperspectral Image Denoising

IEEE transactions on geoscience and remote sensing, 2018-04, Vol.56 (4), p.1940-1958

2018

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Enhanced Sparsity Prior Model for Low-Rank Tensor Completion

IEEE transaction on neural networks and learning systems, 2020-11, Vol.31 (11), p.4567-4581

2020

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Hyper-Laplacian regularized nonlocal low-rank matrix recovery for hyperspectral image compressive sensing reconstruction

Information sciences, 2019-10, Vol.501, p.406-420

2019

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Nonlocal Tensor Sparse Representation and Low-Rank Regularization for Hyperspectral Image Compressive Sensing Reconstruction

Remote sensing (Basel, Switzerland), 2019-01, Vol.11 (2), p.193

2019

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Hyperspectral Image Restoration via Spatial-Spectral Residual Total Variation Regularized Low-Rank Tensor Decomposition

Remote sensing (Basel, Switzerland), 2022-01, Vol.14 (3), p.511

2022

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Hyperspectral Image Denoising Using Global Weighted Tensor Norm Minimum and Nonlocal Low-Rank Approximation

Remote sensing (Basel, Switzerland), 2019-10, Vol.11 (19), p.2281

2019

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Hyperspectral Image Denoising Based on Nonlocal Low-Rank and TV Regularization

Remote sensing (Basel, Switzerland), 2020-06, Vol.12 (12), p.1956

2020

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Global and Local Tensor Sparse Approximation Models for Hyperspectral Image Destriping

Remote sensing (Basel, Switzerland), 2020-02, Vol.12 (4), p.704

2020

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Total Variation and Rank-1 Constraint RPCA for Background Subtraction

IEEE access, 2018-01, Vol.6, p.49955-49966

2018

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Heterogeneous Regularization-Based Tensor Subspace Clustering for Hyperspectral Band Selection

IEEE transaction on neural networks and learning systems, 2023-11, Vol.34 (11), p.9259-9273

2023

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Multilayer Sparsity-Based Tensor Decomposition for Low-Rank Tensor Completion

IEEE transaction on neural networks and learning systems, 2022-11, Vol.33 (11), p.6916-6930

2022

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Tensor Convolution-like Low-Rank Dictionary for High-Dimensional Image Representation

IEEE transactions on circuits and systems for video technology, 2024-08, p.1-1

2024

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Nonconvex tensor rank minimization and its applications to tensor recovery

Information sciences, 2019-11, Vol.503, p.109-128

2019

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A fast correction approach to tensor robust principal component analysis

Applied mathematical modelling, 2024-04, Vol.128, p.195-219

2024

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Low-Rank Tensor Completion Based on Self-Adaptive Learnable Transforms

IEEE transaction on neural networks and learning systems, 2024-07, Vol.35 (7), p.8826-8838

2024

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Specular reflection removal using local structural similarity and chromaticity consistency

2015 IEEE International Conference on Image Processing (ICIP), 2015, p.3397-3401

2015

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When Laplacian Scale Mixture Meets Three-Layer Transform: A Parametric Tensor Sparsity for Tensor Completion

IEEE transactions on cybernetics, 2022-12, Vol.52 (12), p.13887-13901

2022

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Hyperspectral and Multispectral Image Fusion via Graph Laplacian-Guided Coupled Tensor Decomposition

IEEE transactions on geoscience and remote sensing, 2021-01, Vol.59 (1), p.648-662

2021

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Multimodal Core Tensor Factorization and Its Applications to Low-Rank Tensor Completion

IEEE transactions on multimedia, 2023-01, Vol.25, p.1-15

2023

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Depressformer: Leveraging Video Swin Transformer and fine-grained local features for depression scale estimation

Biomedical signal processing and control, 2024-10, Vol.96 (Part A), p.106490, Article 106490

2024

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Transferable Multiple Subspace Learning for Hyperspectral Image Super-Resolution

IEEE geoscience and remote sensing letters, 2024, Vol.21, p.1-5

2024

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Transformed Structured Sparsity With Smoothness for Hyperspectral Image Deblurring

IEEE geoscience and remote sensing letters, 2023, Vol.20, p.1-5

2023

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Rank-1 Tensor Decomposition for Hyperspectral Image Denoising with Nonlocal Low-Rank Regularization

2017 International Conference on Machine Vision and Information Technology (CMVIT), 2017, p.40-45

2017

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Nonlocal Low-Rank Regularized Tensor Decomposition for Hyperspectral Image Denoising

Spatial-Spectral Structured Sparse Low-Rank Representation for Hyperspectral Image Super-Resolution

Joint Spatial and Spectral Low-Rank Regularization for Hyperspectral Image Denoising

Enhanced Sparsity Prior Model for Low-Rank Tensor Completion

Hyper-Laplacian regularized nonlocal low-rank matrix recovery for hyperspectral image compressive sensing reconstruction

Nonlocal Tensor Sparse Representation and Low-Rank Regularization for Hyperspectral Image Compressive Sensing Reconstruction

Hyperspectral Image Restoration via Spatial-Spectral Residual Total Variation Regularized Low-Rank Tensor Decomposition

Hyperspectral Image Denoising Using Global Weighted Tensor Norm Minimum and Nonlocal Low-Rank Approximation

Hyperspectral Image Denoising Based on Nonlocal Low-Rank and TV Regularization

Global and Local Tensor Sparse Approximation Models for Hyperspectral Image Destriping

Total Variation and Rank-1 Constraint RPCA for Background Subtraction

Heterogeneous Regularization-Based Tensor Subspace Clustering for Hyperspectral Band Selection

Multilayer Sparsity-Based Tensor Decomposition for Low-Rank Tensor Completion

Tensor Convolution-like Low-Rank Dictionary for High-Dimensional Image Representation

Nonconvex tensor rank minimization and its applications to tensor recovery

A fast correction approach to tensor robust principal component analysis

Low-Rank Tensor Completion Based on Self-Adaptive Learnable Transforms

Specular reflection removal using local structural similarity and chromaticity consistency

When Laplacian Scale Mixture Meets Three-Layer Transform: A Parametric Tensor Sparsity for Tensor Completion

Hyperspectral and Multispectral Image Fusion via Graph Laplacian-Guided Coupled Tensor Decomposition

Multimodal Core Tensor Factorization and Its Applications to Low-Rank Tensor Completion

Depressformer: Leveraging Video Swin Transformer and fine-grained local features for depression scale estimation

Transferable Multiple Subspace Learning for Hyperspectral Image Super-Resolution

Transformed Structured Sparsity With Smoothness for Hyperspectral Image Deblurring

Rank-1 Tensor Decomposition for Hyperspectral Image Denoising with Nonlocal Low-Rank Regularization

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