Centroidal Voronoi tessellation algorithms for image compression, segmentation, and multichannel restoration

DOI10.1007/s10851-005-3620-4zbMath1478.94033OpenAlexW2010495532WikidataQ113106958 ScholiaQ113106958MaRDI QIDQ2491353

Lili Ju, Qiang Du, Max D. Gunzburger, Xiaoqiang Wang

Publication date: 29 May 2006

Published in: Journal of Mathematical Imaging and Vision (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10851-005-3620-4

zbMATH Keywords

image compressionimage segmentationedge detectionimage restorationk-meanscentroidal Voronoi tessellations

Mathematics Subject Classification ID

Computing methodologies for image processing (68U10) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Tilings in (n) dimensions (aspects of discrete geometry) (52C22)

Related Items

Generalized edge-weighted centroidal Voronoi tessellations for geometry processing, Centroidal Voronoi tessellation based polycube construction for adaptive all-hexahedral mesh generation, Defects and frustration in the packing of soft balls, An Active Contour Model with Local Variance Force Term and Its Efficient Minimization Solver for Multiphase Image Segmentation, Asymptotic optimality of the triangular lattice for a class of optimal location problems, A fuzzy edge-weighted centroidal Voronoi tessellation model for image segmentation, Adaptive tetrahedral mesh generation by constrained centroidal voronoi‐delaunay tessellations for finite element methods, Stochastic finite element methods for partial differential equations with random input data, Surface segmentation for polycube construction based on generalized centroidal Voronoi tessellation, A Characteristic Function-Based Algorithm for Geodesic Active Contours, Fast methods for computing centroidal Voronoi tessellations

Uses Software

• AS 58
• AS 136

Cites Work

• Algorithm AS 136: A K-Means Clustering Algorithm
• Meshfree, probabilistic determination of point sets and support regions for meshless computing
• Probabilistic methods for centroidal Voronoi tessellations and their parallel implementations
• A multiphase level set framework for image segmentation using the Mumford and Shah model
• Active contours without edges
• Constrained Centroidal Voronoi Tessellations for Surfaces
• Centroidal Voronoi Tessellations: Applications and Algorithms
• The analysis of a simple k -means clustering algorithm
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item