research-article

Remote sensing images destriping using unidirectional hybrid total variation and nonconvex low-rank regularization

Authors:

Ting-Zhu Huang,

Meng DingAuthors Info & Claims

Volume 363, Issue C

Pages 124 - 144

https://doi.org/10.1016/j.cam.2019.06.004

Published: 01 January 2020 Publication History

Abstract

In this paper, we propose a novel model for remote sensing images destriping, which includes the Schatten 1 ∕ 2-norm and the unidirectional first-order and high-order total variation regularization. The main idea is that the stripe layer is low-rank, and the desired image possesses smoothness across stripes. Therefore, we use the Schatten 1 ∕ 2-norm regularization to depict the low-rankness of stripes, and use the unidirectional total variation and the unidirectional high-order total variation to guarantee the smoothness of the underlying image. We develop the alternating direction method of multipliers algorithm to solve the proposed model. Extensive experiments on synthetic and real data are reported to show the superiority of the proposed method over state-of-the-art methods in terms of both quantitative and qualitative assessments.

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Cited By

Li RZheng B(2024)Tensor completion via multi-directional partial tensor nuclear norm with total variation regularizationCalcolo: a quarterly on numerical analysis and theory of computation10.1007/s10092-024-00569-161:2Online publication date: 4-Mar-2024
https://dl.acm.org/doi/10.1007/s10092-024-00569-1
Tan HKong WZhang FQin WWang JEl Saddik AMei TCucchiara RBertini MTobon Vallejo DAtrey PHossain M(2023)High-Order Tensor Recovery Coupling Multilayer Subspace Priori with Application in Video RestorationProceedings of the 31st ACM International Conference on Multimedia10.1145/3581783.3613790(1212-1220)Online publication date: 26-Oct-2023
https://dl.acm.org/doi/10.1145/3581783.3613790
Zhao XYang JMa TJiang TNg MHuang T(2022)Tensor Completion via Complementary Global, Local, and Nonlocal PriorsIEEE Transactions on Image Processing10.1109/TIP.2021.313832531(984-999)Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1109/TIP.2021.3138325
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Remote sensing images destriping using unidirectional hybrid total variation and nonconvex low-rank regularization

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Published In

cover image Journal of Computational and Applied Mathematics

Journal of Computational and Applied Mathematics Volume 363, Issue C

Jan 2020

503 pages

ISSN:0377-0427

Issue’s Table of Contents

Elsevier B.V.

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Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 January 2020

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Cited By

Li RZheng B(2024)Tensor completion via multi-directional partial tensor nuclear norm with total variation regularizationCalcolo: a quarterly on numerical analysis and theory of computation10.1007/s10092-024-00569-161:2Online publication date: 4-Mar-2024
https://dl.acm.org/doi/10.1007/s10092-024-00569-1
Tan HKong WZhang FQin WWang JEl Saddik AMei TCucchiara RBertini MTobon Vallejo DAtrey PHossain M(2023)High-Order Tensor Recovery Coupling Multilayer Subspace Priori with Application in Video RestorationProceedings of the 31st ACM International Conference on Multimedia10.1145/3581783.3613790(1212-1220)Online publication date: 26-Oct-2023
https://dl.acm.org/doi/10.1145/3581783.3613790
Zhao XYang JMa TJiang TNg MHuang T(2022)Tensor Completion via Complementary Global, Local, and Nonlocal PriorsIEEE Transactions on Image Processing10.1109/TIP.2021.313832531(984-999)Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1109/TIP.2021.3138325
Li XHuang TZhao XJi TZheng YDeng L(2021)Adaptive total variation and second-order total variation-based model for low-rank tensor completionNumerical Algorithms10.1007/s11075-020-00876-y86:1(1-24)Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.1007/s11075-020-00876-y
Lin XNg MZhao X(2020)Tensor Factorization with Total Variation and Tikhonov Regularization for Low-Rank Tensor Completion in Imaging DataJournal of Mathematical Imaging and Vision10.1007/s10851-019-00933-962:6-7(900-918)Online publication date: 1-Jul-2020
https://dl.acm.org/doi/10.1007/s10851-019-00933-9

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