Coloured Voronoi tessellations for Bayesian image analysis and reservoir modelling

被引：11

作者：

Moller, Jesper ^{[1
]}

Skare, Oivind ^{[2
,3
]}

机构：

[1] Aalborg Univ, Dept Math Sci, DK-9220 Aalborg, Denmark

[2] Norwegian Comp Ctr, Oslo, Norway

[3] Univ Oslo, Dept Biol, Oslo, Norway

来源：

STATISTICAL MODELLING | 2001年 / 1卷 / 03期

基金：

新加坡国家研究基金会;

关键词：

Markov chain Monte Carlo; Markov connected component fields; Markov random fields; nearest-neighbour Markov point processes; polygonal partitions; three-dimensional image analysis; triangulation models;

D O I：

10.1177/1471082X0100100304

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

A new flexible prior for Bayesian image analysis and reservoir modelling is defined in terms of interacting coloured Voronoi cells described by a certain nearest-neighbour Markov point process. This prior can be defined in both two and three (as well as higher) dimensions, and simple MCMC algorithms can be used for drawing inference from the posterior distribution. Various 2D and 3D applications are considered.

引用

页码：213 / 232

页数：20

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