bayesImageS: Bayesian Methods for Image Segmentation using a Potts Model
Version 0.5-1

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 . 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 Bayesian indirect likelihood (BIL). Refer to and for further details.

Package details

AuthorMatt Moores [aut, cre] (<>), Kerrie Mengersen [aut, ths] (<>), Dai Feng [ctb]
Date of publication2018-02-02 16:32:10 UTC
MaintainerMatt Moores <[email protected]>
LicenseGPL (>= 2)
Package repositoryView on CRAN
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bayesImageS documentation built on Feb. 2, 2018, 5:03 p.m.