bayesImageS: Bayesian Methods for Image Segmentation using a Potts Model
Version 0.4-0

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. Latent labels are sampled using chequerboard updating or Swendsen-Wang. Algorithms for the smoothing parameter include pseudolikelihood, path sampling, the exchange algorithm, and approximate Bayesian computation (ABC).

Package details

AuthorMatt Moores [aut, cre], Kerrie Mengersen [aut], Dai Feng [ctb]
Date of publication2017-03-21 15:13:30 UTC
MaintainerMatt Moores <M.T.Moores@warwick.ac.uk>
LicenseGPL (>= 2)
Version0.4-0
URL https://bitbucket.org/Azeari/bayesimages
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("bayesImageS")

Try the bayesImageS package in your browser

Any scripts or data that you put into this service are public.

bayesImageS documentation built on May 30, 2017, 2:49 a.m.