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
fDate :
6/23/1905 12:00:00 AM
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;
Conference_Titel :
Statistical Signal Processing, 2001. Proceedings of the 11th IEEE Signal Processing Workshop on
Print_ISBN :
0-7803-7011-2
DOI :
10.1109/SSP.2001.955212
