Bounded Variation Regularization Using Line Sections

DOI10.1080/01630560902841161zbMath1183.68688OpenAlexW2120922765MaRDI QIDQ3630404

Stefan Kindermann

Publication date: 29 May 2009

Published in: Numerical Functional Analysis and Optimization (Search for Journal in Brave)

Full work available at URL: http://www.informaworld.com/smpp/./content~db=all~content=a910367409

zbMATH Keywords

bounded variationCrofton formulaline sectionsROF-functional

Mathematics Subject Classification ID

Numerical methods involving duality (49M29) Numerical optimization and variational techniques (65K10) Computing methodologies for image processing (68U10) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Geometric measure and integration theory, integral and normal currents in optimization (49Q15)

Cites Work

• Nonlinear total variation based noise removal algorithms
• Tube methods for BV regularization
• Image recovery via total variation minimization and related problems
• Image sharpening by flows based on triple well potentials
• Augmented Lagrangian methods for nonsmooth, convex optimization in Hilbert spaces
• Geometric measure theory.
• Denoising by BV-duality
• The Mathematics of Computerized Tomography
• Optimal approximations by piecewise smooth functions and associated variational problems
• Algorithms for Finding Global Minimizers of Image Segmentation and Denoising Models
• A Second Order Shape Optimization Approach for Image Segmentation
• Minimizers of Cost-Functions Involving Nonsmooth Data-Fidelity Terms. Application to the Processing of Outliers
• Second-order Cone Programming Methods for Total Variation-Based Image Restoration
• An Iterative Regularization Method for Total Variation-Based Image Restoration
• Image Processing and Analysis
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