Nonconvex TGV regularization model for multiplicative noise removal with spatially varying parameters
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Publication:667778
DOI10.3934/ipi.2019007zbMath1491.94009OpenAlexW2903984188WikidataQ128706053 ScholiaQ128706053MaRDI QIDQ667778
Miyoun Jung, Myeongmin Kang, Myungjoo Kang, Hanwool Na
Publication date: 1 March 2019
Published in: Inverse Problems and Imaging (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.3934/ipi.2019007
image denoisingalternating direction method of multiplieriteratively reweighted \(\ell_1\) algorithmmultiplicative gamma noisenonconvex total generalized variationspatially adaptive regularization parameter
Numerical optimization and variational techniques (65K10) Computing methodologies for image processing (68U10) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)
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Cites Work
- Nonlinear total variation based noise removal algorithms
- Convex image denoising via non-convex regularization with parameter selection
- Operator splittings, Bregman methods and frame shrinkage in image processing
- A convex total generalized variation regularized model for multiplicative noise and blur removal
- Enhancing sparsity by reweighted \(\ell _{1}\) minimization
- Multiplicative noise removal in imaging: an exp-model and its fixed-point proximity algorithm
- On semi- and subanalytic geometry
- Image recovery via total variation minimization and related problems
- An exp model with spatially adaptive regularization parameters for multiplicative noise removal
- Automated regularization parameter selection in multi-scale total variation models for image restoration
- A first-order primal-dual algorithm for convex problems with applications to imaging
- Convergence of descent methods for semi-algebraic and tame problems: proximal algorithms, forward-backward splitting, and regularized Gauss-Seidel methods
- Fast linearized alternating direction minimization algorithm with adaptive parameter selection for multiplicative noise removal
- High-order TVL1-based images restoration and spatially adapted regularization parameter selection
- A TV based restoration model with local constraints
- Linearly Constrained Nonsmooth and Nonconvex Minimization
- Two-Level Convex Relaxed Variational Model for Multiplicative Denoising
- A Convex Variational Model for Restoring Blurred Images with Multiplicative Noise
- A New Detail-Preserving Regularization Scheme
- Alternating Direction Algorithms for $\ell_1$-Problems in Compressive Sensing
- A Nonlinear Inverse Scale Space Method for a Convex Multiplicative Noise Model
- The Split Bregman Method for L1-Regularized Problems
- Spatially adapted regularization parameter selection based on the local discrepancy function for Poissonian image deblurring
- A Variational Approach to Removing Multiplicative Noise
- Noise removal using fourth-order partial differential equation with applications to medical magnetic resonance images in space and time
- High-Order Total Variation-Based Image Restoration
- Speckle Reduction via Higher Order Total Variation Approach
- Convergence rate bounds for a proximal ADMM with over-relaxation stepsize parameter for solving nonconvex linearly constrained problems
- Convergence of alternating direction method for minimizing sum of two nonconvex functions with linear constraints
- Multiplicative Noise Removal with Spatially Varying Regularization Parameters
- On Iteratively Reweighted Algorithms for Nonsmooth Nonconvex Optimization in Computer Vision
- Proximal Linearized Alternating Direction Method for Multiplicative Denoising
- Fast Nonconvex Nonsmooth Minimization Methods for Image Restoration and Reconstruction
- Spatially Adapted Total Variation Model to Remove Multiplicative Noise
- The Łojasiewicz Inequality for Nonsmooth Subanalytic Functions with Applications to Subgradient Dynamical Systems
- Model completeness results for expansions of the ordered field of real numbers by restricted Pfaffian functions and the exponential function
- Total Generalized Variation
