New time dependent pretreat models based on total variational image restoration

DOI10.1007/s10255-011-0046-1zbMath1207.68431OpenAlexW2094698861WikidataQ113107427 ScholiaQ113107427MaRDI QIDQ628639

Jing Xu, Qian-shun Chang

Publication date: 14 March 2011

Published in: Acta Mathematicae Applicatae Sinica. English Series (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10255-011-0046-1

zbMATH Keywords

total variationanisotropic diffusionimage restorationlevel set motionPSNR

Mathematics Subject Classification ID

Computing methodologies for image processing (68U10) Numerical methods for variational inequalities and related problems (65K15)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Nonlinear total variation based noise removal algorithms
• Network flow optimization for restoration of images
• Fronts propagating with curvature-dependent speed: Algorithms based on Hamilton-Jacobi formulations
• Image recovery via total variation minimization and related problems
• Image restoration with discrete constrained total variation. I: Fast and exact optimization
• New time dependent model for image restoration
• Accurate partial difference methods. II: Non-linear problems
• An Optimization‐Based Multilevel Algorithm for Total Variation Image Denoising
• Noise Removal Using Smoothed Normals and Surface Fitting
• Augmented Lagrangian Method, Dual Methods and Split Bregman Iteration for ROF Model
• Image Selective Smoothing and Edge Detection by Nonlinear Diffusion
• Image Selective Smoothing and Edge Detection by Nonlinear Diffusion. II
• A Nonlinear Primal-Dual Method for Total Variation-Based Image Restoration
• Analysis of bounded variation penalty methods for ill-posed problems
• A Variational Method in Image Recovery
• Acceleration Methods for Total Variation-Based Image Denoising
• A Note on Antireflective Boundary Conditions and Fast Deblurring Models
• Explicit Algorithms for a New Time Dependent Model Based on Level Set Motion for Nonlinear Deblurring and Noise Removal
• A Fast Algorithm for Deblurring Models with Neumann Boundary Conditions
• Iterative Methods for Total Variation Denoising
• Aspects of Total Variation RegularizedL¹Function Approximation
• Second-order Cone Programming Methods for Total Variation-Based Image Restoration
• Efficient Minimization Methods of Mixed l2-l1 and l1-l1 Norms for Image Restoration
• On the Construction and Comparison of Difference Schemes

This page was built for publication: New time dependent pretreat models based on total variational image restoration