An improved and accelerated non-linear multigrid method for total-variation denoising

DOI10.1080/00207160500069904zbMath1072.65096OpenAlexW1990274520MaRDI QIDQ5462892

Joseph Savage, Ke Chen

Publication date: 27 July 2005

Published in: International Journal of Computer Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207160500069904

zbMATH Keywords

algorithmtotal variationconvergencenumerical examplesdiscontinuous coefficientssmoothersmultigrid methodsdenoisingimage restorationKrylov acceleration

Mathematics Subject Classification ID

Numerical optimization and variational techniques (65K10) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Decomposition methods (49M27) Existence theories for optimal control problems involving partial differential equations (49J20)

Related Items (13)

Improved variational image registration model and a fast algorithm for its numerical approximation ⋮ A weightedH¹seminorm regularization method for Fredholm integral equations of the first kind ⋮ Domain decomposition methods with graph cuts algorithms for total variation minimization ⋮ An Efficient Numerical Method for Mean Curvature-Based Image Registration Model ⋮ A robust multigrid approach for variational image registration models ⋮ A nonlinear multigrid method for total variation minimization from image restoration ⋮ An efficient multi-grid method for TV minimization problems ⋮ On a nonlinear multigrid algorithm with primal relaxation for the image total variation minimisation ⋮ An improved discontinuity-preserving image registration model and its fast algorithm ⋮ An accelerated algebraic multigrid algorithm for total-variation denoising ⋮ A new variational model for removal of combined additive and multiplicative noise and a fast algorithm for its numerical approximation ⋮ A vectorial minimized surface regularizer based image registration model and its numerical algorithm ⋮ A restarted iterative homotopy analysis method for two nonlinear models from image processing

Uses Software

• Wesseling

Cites Work

• Nonlinear total variation based noise removal algorithms
• A Nonlinear Primal-Dual Method for Total Variation-Based Image Restoration
• Explicit Algorithms for a New Time Dependent Model Based on Level Set Motion for Nonlinear Deblurring and Noise Removal
• Computational Methods for Inverse Problems
• Iterative Methods for Total Variation Denoising
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