• DocumentCode
    2231762
  • Title

    Unsupervised segmentation of textured satellite and aerial images with Bayesian methods

  • Author

    Wilson, Simon P. ; Zerubia, Josiane

  • Author_Institution
    Dept. of Stat., Trinity Coll., Dublin, Ireland
  • fYear
    2002
  • fDate
    3-6 Sept. 2002
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    We investigate Bayesian solutions to unsupervised image segmentation based on the double Markov random field model. Inference on the number of classes in the image is done with reversible jump Metropolis moves. These moves are implemented by splitting and merging classes. Tests are conducted on satellite and aerial images.
  • Keywords
    Bayes methods; Markov processes; geophysical image processing; image segmentation; image texture; remote sensing; Bayesian method; Markov random field model; aerial images; merging class; satellite image texture; splitting class; unsupervised image segmentation; Abstracts; Bayes methods; Image segmentation; Markov processes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing Conference, 2002 11th European
  • Conference_Location
    Toulouse
  • ISSN
    2219-5491
  • Type

    conf

  • Filename
    7071914
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2231762