DocumentCode
2464836
Title
A multiresolution EM algorithm for unsupervised image classification
Author
Laferte, J.-M. ; Heitz, F. ; Perez, Pablo
Author_Institution
IRISA-INRIA, Rennes I Univ.
Volume
2
fYear
1996
fDate
25-29 Aug 1996
Firstpage
849
Abstract
Using the causal Markov model defined on a quadtree we derive a multiresolution EM algorithm for unsupervised image classification. This algorithm is an efficient alternative to expensive or approximate EM algorithms associated with Markov random fields (MRFs). We show on synthetic and real images that our algorithm also provides good or even better results than those obtained by spatial MRF models
Keywords
hidden Markov models; image classification; iterative methods; maximum likelihood estimation; quadtrees; causal Markov model; expectation-maximization algorithm; iterative methods; maximum likelihood estimation; multiresolution EM algorithm; parameter estimation; quadtree; unsupervised image classification; Classification algorithms; Computer vision; Hidden Markov models; Image classification; Image resolution; Iterative algorithms; Markov random fields; Maximum likelihood estimation; Spatial resolution; Stochastic processes;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 1996., Proceedings of the 13th International Conference on
Conference_Location
Vienna
ISSN
1051-4651
Print_ISBN
0-8186-7282-X
Type
conf
DOI
10.1109/ICPR.1996.547196
Filename
547196
Link To Document