Geometric applications of the split Bregman method: segmentation and surface reconstruction

DOI10.1007/s10915-009-9331-zzbMath1203.65044OpenAlexW2135095945MaRDI QIDQ618628

Tom Goldstein, Xavier Bresson, Stanley J. Osher

Publication date: 16 January 2011

Published in: Journal of Scientific Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10915-009-9331-z

Mathematics Subject Classification ID

Computing methodologies for image processing (68U10) Numerical aspects of computer graphics, image analysis, and computational geometry (65D18) Computational issues in computer and robotic vision (65D19)

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Uses Software

• RecPF

Cites Work

• Nonlinear total variation based noise removal algorithms
• Fronts propagating with curvature-dependent speed: Algorithms based on Hamilton-Jacobi formulations
• A level set approach for computing solutions to incompressible two-phase flow
• Geodesic active contours
• Regularized Laplacian zero crossings as optimal edge integrators
• An algorithm for total variation minimization and applications
• Surface reconstruction by Voronoi filtering
• Level set methods and dynamic implicit surfaces
• An algorithm for mean curvature motion
• A fast level set method for propagating interfaces
• Thevenin decomposition and large-scale optimization
• Dual norms and image decomposition models
• Optimal approximations by piecewise smooth functions and associated variational problems
• Adapting to Unknown Smoothness via Wavelet Shrinkage
• A New Alternating Minimization Algorithm for Total Variation Image Reconstruction
• Algorithms for Finding Global Minimizers of Image Segmentation and Denoising Models
• A Nonlinear Primal-Dual Method for Total Variation-Based Image Restoration
• Active contours without edges
• Curvature-Driven Flows: A Variational Approach
• Implicit and Nonparametric Shape Reconstruction from Unorganized Data Using a Variational Level Set Method
• Bregman Iterative Algorithms for $\ell_1$-Minimization with Applications to Compressed Sensing
• An Iterative Regularization Method for Total Variation-Based Image Restoration
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