Image restoration based on the minimized surface regularization
From MaRDI portal
Publication:2202971
DOI10.1016/j.camwa.2018.07.037zbMath1442.94014OpenAlexW2885413880WikidataQ113103572 ScholiaQ113103572MaRDI QIDQ2202971
Publication date: 1 October 2020
Published in: Computers \& Mathematics with Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.camwa.2018.07.037
image restorationprimal dual methodconvex conjugateminimized surface regularizationsmoothing ROF model
Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)
Related Items
Image denoising based on a new anisotropic mean curvature model ⋮ A vectorial minimized surface regularizer based image registration model and its numerical algorithm
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Nonlinear total variation based noise removal algorithms
- Duality-based algorithms for total-variation-regularized image restoration
- Multiplicative noise removal in imaging: an exp-model and its fixed-point proximity algorithm
- Preconditioned Douglas-Rachford algorithms for TV- and TGV-regularized variational imaging problems
- An algorithm for image removals and decompositions without inverse matrices
- Adaptive total variation image deblurring: a majorization-minimization approach
- An algorithm for total variation minimization and applications
- Images as embedded maps and minimal surfaces: Movies, color, texture, and volumetric medical images
- A first-order primal-dual algorithm for convex problems with applications to imaging
- Augmented Lagrangian method for a mean curvature based image denoising model
- On the $O(1/n)$ Convergence Rate of the Douglas–Rachford Alternating Direction Method
- Convergence Analysis of Primal-Dual Algorithms for a Saddle-Point Problem: From Contraction Perspective
- Inexact Alternating Direction Methods for Image Recovery
- Nonlocal Operators with Applications to Image Processing
- The Split Bregman Method for L1-Regularized Problems
- Augmented Lagrangian Method, Dual Methods, and Split Bregman Iteration for ROF, Vectorial TV, and High Order Models
- Deblurring Methods Using Antireflective Boundary Conditions
- A Nonlinear Primal-Dual Method for Total Variation-Based Image Restoration
- The Use of the L-Curve in the Regularization of Discrete Ill-Posed Problems
- Variational Analysis
- A general framework for low level vision
- Kronecker Product Approximations forImage Restoration with Reflexive Boundary Conditions
- Prox-Method with Rate of Convergence O(1/t) for Variational Inequalities with Lipschitz Continuous Monotone Operators and Smooth Convex-Concave Saddle Point Problems
- A Fast Algorithm for Deblurring Models with Neumann Boundary Conditions
- Computational Methods for Inverse Problems
- Iterative Methods for Total Variation Denoising
- Rate of Convergence Analysis of Decomposition Methods Based on the Proximal Method of Multipliers for Convex Minimization
- Handbook of Mathematical Methods in Imaging
- A Review of Image Denoising Algorithms, with a New One
- Image Processing and Analysis