Low Rank and Total Variation Based Two-Phase Method for Image Deblurring with Salt-and-Pepper Impulse Noise

DOI10.4208/nmtma.oa-2022-0190OpenAlexW4387137171MaRDI QIDQ6151344

Shirong Deng, Yu-Chao Tang, Tieyong Zeng

Publication date: 11 March 2024

Published in: Numerical Mathematics: Theory, Methods and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.4208/nmtma.oa-2022-0190

zbMATH Keywords

total variationnuclear normimage deblurringimpulse noise

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Convex programming (90C25) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Cites Work

• Unnamed Item
• Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
• Augmented Lagrangian method for total variation restoration with non-quadratic fidelity
• A first-order primal-dual algorithm for convex problems with applications to imaging
• Sparse representation based image deblurring model under random-valued impulse noise
• A ``nonconvex+nonconvex approach for image restoration with impulse noise removal
• Depression disorder classification of fMRI data using sparse low-rank functional brain network and graph-based features
• Generalized alternating direction method of multipliers: new theoretical insights and applications
• Constrained Total Variation Deblurring Models and Fast Algorithms Based on Alternating Direction Method of Multipliers
• Sparse Representation Prior and Total Variation--Based Image Deblurring under Impulse Noise
• A Singular Value Thresholding Algorithm for Matrix Completion
• A General Framework for a Class of First Order Primal-Dual Algorithms for Convex Optimization in Imaging Science
• Nonconvex-TV Based Image Restoration with Impulse Noise Removal
• Total Variation Based Parameter-Free Model for Impulse Noise Removal
• A Fast $\ell$1-TV Algorithm for Image Restoration
• Fast Multilevel Algorithm for a Minimization Problem in Impulse Noise Removal
• A TVSCAD approach for image deblurring with impulsive noise
• Non-Lipschitz Models for Image Restoration with Impulse Noise Removal
• Aspects of Total Variation RegularizedL¹Function Approximation
• An Efficient Two-Phase ${\rm L}^{1}$-TV Method for Restoring Blurred Images with Impulse Noise
• Efficient Box-Constrained TV-Type-l¹ Algorithms for Restoring Images with Impulse Noise
• A Convex and Exact Approach to Discrete Constrained TV-L1 Image Approximation
• Efficient Minimization Methods of Mixed l2-l1 and l1-l1 Norms for Image Restoration
• Convex analysis and monotone operator theory in Hilbert spaces

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