bayesImageS
Bayesian Methods for Image Segmentation using a Potts Model
Description
Various algorithms for segmentation of 2D and 3D images, such as computed tomography and satellite remote sensing. This package implements Bayesian image analysis using the hidden Potts model with external field prior of Moores et al. (2015) <doi:10.1016/j.csda.2014.12.001>. Latent labels are sampled using chequerboard updating or Swendsen-Wang. Algorithms for the smoothing parameter include pseudolikelihood, path sampling, the exchange algorithm, approximate Bayesian computation (ABC-MCMC and ABC-SMC), and the parametric functional approximate Bayesian (PFAB) algorithm. Refer to Moores, Pettitt & Mengersen (2020) <doi:10.1007/978-3-030-42553-1_6> for an overview and also to <doi:10.1007/s11222-014-9525-6> and <doi:10.1214/18-BA1130> for further details of specific algorithms.
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| r-devel-windows-x86_64 | OK |
| r-oldrel-macos-arm64 | NOTE |
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| r-oldrel-windows-x86_64 | OK |
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installed package size
installed size is 7.6Mb
sub-directories of 1Mb or more:
data 2.7Mb
libs 4.5Mb
installed package size
installed size is 8.1Mb
sub-directories of 1Mb or more:
data 3.1Mb
libs 4.5Mb
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NOTE 12 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026
installed package size
installed size is 7.6Mb
sub-directories of 1Mb or more:
data 2.7Mb
libs 4.5Mb
installed package size
installed size is 8.1Mb
sub-directories of 1Mb or more:
data 3.1Mb
libs 4.5Mb