Memory-efficient categorical multi-point statistics algorithms based on compact search trees

DOI10.1007/s11004-012-9412-7zbMath1383.62181OpenAlexW2075232741MaRDI QIDQ1929975

Christen Knudby, Tuanfeng Zhang, Stein Inge Pedersen, David S. McCormick

Publication date: 10 January 2013

Published in: Mathematical Geosciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11004-012-9412-7

zbMATH Keywords

training imagesmulti-point statisticscompact search treeconventional search tree

Mathematics Subject Classification ID

Searching and sorting (68P10) Image analysis in multivariate analysis (62H35) Computing methodologies for image processing (68U10)

Related Items (2)

Construction of binary multi-grid Markov random field prior models from training images ⋮ CDFSIM: efficient stochastic simulation through decomposition of cumulative distribution functions of transformed spatial patterns

Uses Software

• GSLIB

Cites Work

• An improved parallel multiple-point algorithm using a list approach
• Conditional simulation of complex geological structures using multiple-point statistics

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