Completely convex formulation of the Chan-Vese image segmentation model

DOI10.1007/s11263-011-0499-yzbMath1254.68271OpenAlexW2165351422WikidataQ57397268 ScholiaQ57397268MaRDI QIDQ1931580

Tony F. Chan, Xavier Bresson, Ethan S. Brown

Publication date: 15 January 2013

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

Full work available at URL: https://doi.org/10.1007/s11263-011-0499-y

zbMATH Keywords

level set methodimage segmentationconvex relaxation\(K\)-meansChan-Vese modelvector-valued functional lifting

Mathematics Subject Classification ID

Convex programming (90C25) Machine vision and scene understanding (68T45)

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Cites Work

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• Global minimization for continuous multiphase partitioning problems using a dual approach
• Geometric applications of the split Bregman method: segmentation and surface reconstruction
• An integral formula for total gradient variation
• Fronts propagating with curvature-dependent speed: Algorithms based on Hamilton-Jacobi formulations
• A first-order primal-dual algorithm for convex problems with applications to imaging
• Global minimization of Markov random fields with applications to optical flow
• Optimal approximations by piecewise smooth functions and associated variational problems
• A General Framework for a Class of First Order Primal-Dual Algorithms for Convex Optimization in Imaging Science
• Global Solutions of Variational Models with Convex Regularization
• Continuous Multiclass Labeling Approaches and Algorithms
• Curvature Measures
• Algorithms for Finding Global Minimizers of Image Segmentation and Denoising Models
• A binary level set model and some applications to Mumford-Shah image segmentation
• Graph Cut Optimization for the Piecewise Constant Level Set Method Applied to Multiphase Image Segmentation
• Maximal flow through a domain
• The calibration method for the mumford-shah functional
• Active contours without edges

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