Split Bregman iteration algorithm for total bounded variation regularization based image deblurring

DOI10.1016/j.jmaa.2010.07.013zbMath1202.94062OpenAlexW2051974992MaRDI QIDQ994320

Xinwu Liu, Li-Hong Huang

Publication date: 17 September 2010

Published in: Journal of Mathematical Analysis and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmaa.2010.07.013

zbMATH Keywords

image deblurringsplit Bregman iteration\texttt{MATLAB}total bounded variation

Mathematics Subject Classification ID

Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Related Items (13)

Total bounded variation-based Poissonian images recovery by split Bregman iteration ⋮ Split Bregman iteration algorithm for image deblurring using fourth-order total bounded variation regularization model ⋮ Multi and hyperspectral image unmixing with spatial coherence by extended blind end-member and abundance extraction ⋮ Fixed-Point-like method for a new Total variation-based image restoration model ⋮ A PDE approach to image restoration problem with observation on a meager domain ⋮ A new nonlocal total variation regularization algorithm for image denoising ⋮ Runge-Kutta type total variation regularization for nonlinear inverse problems ⋮ Efficient algorithms for hybrid regularizers based image denoising and deblurring ⋮ An efficient variational method for image restoration ⋮ An augmented Lagrangian algorithm for total bounded variation regularization based image deblurring ⋮ An efficient algorithm for adaptive total variation based image decomposition and restoration ⋮ CT image reconstruction algorithms based on the Hanke Raus parameter choice rule ⋮ Non-local total bounded variation scheme for multiple-coil magnetic resonance image restoration

Uses Software

• Matlab
• RecPF

Cites Work

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• Nonlinear total variation based noise removal algorithms
• Image recovery via total variation minimization and related problems
• Linearized Bregman iterations for compressed sensing
• Convergence of the linearized Bregman iteration for ℓ₁-norm minimization
• A New Alternating Minimization Algorithm for Total Variation Image Reconstruction
• Linearized Bregman Iterations for Frame-Based Image Deblurring
• The Split Bregman Method for L1-Regularized Problems
• Nonlinear iterative methods for linear ill-posed problems in Banach spaces
• Split Bregman Methods and Frame Based Image Restoration
• Bregmanized Nonlocal Regularization for Deconvolution and Sparse Reconstruction
• Applications of a Splitting Algorithm to Decomposition in Convex Programming and Variational Inequalities
• On the Convergence of the Lagged Diffusivity Fixed Point Method in Total Variation Image Restoration
• A Nonlinear Primal-Dual Method for Total Variation-Based Image Restoration
• Analysis of bounded variation penalty methods for ill-posed problems
• Regularization of linear least squares problems by total bounded variation
• Total Bounded Variation Regularization as a Bilaterally Constrained Optimization Problem
• Iterative Methods for Total Variation Denoising
• Bregman Iterative Algorithms for $\ell_1$-Minimization with Applications to Compressed Sensing
• Signal Recovery by Proximal Forward-Backward Splitting
• An Iterative Regularization Method for Total Variation-Based Image Restoration

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