• DocumentCode
    1606411
  • Title

    Parameter estimation by a Markov chain Monte Carlo technique for the Candy model

  • Author

    Descombes, X. ; van Lieshout, M.N.M. ; Stoica, R. ; Zerubia, J.

  • Author_Institution
    INRIA, Sophia Antipolis, France
  • fYear
    2001
  • fDate
    6/23/1905 12:00:00 AM
  • Firstpage
    22
  • Lastpage
    25
  • Abstract
    This paper presents a parameter estimation method for the Candy model based on Monte Carlo approximation of the likelihood function. In order to produce such an approximation a Metropolis-Hastings style algorithm for simulating the Candy model is introduced
  • Keywords
    Markov processes; Monte Carlo methods; image processing; maximum likelihood estimation; Candy model; MLE; Markov chain Monte Carlo technique; Metropolis-Hastings style algorithm; Monte Carlo approximation; high-level image analysis; image processing; likelihood function; maximum likelihood estimation; parameter estimation; parameter estimation method; Image color analysis; Image processing; Image resolution; Image segmentation; Kernel; Monte Carlo methods; Parameter estimation; Pixel; Rivers; Roads;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Statistical Signal Processing, 2001. Proceedings of the 11th IEEE Signal Processing Workshop on
  • Print_ISBN
    0-7803-7011-2
  • Type

    conf

  • DOI
    10.1109/SSP.2001.955212
  • Filename
    955212
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1606411