@inbook {1240,
	title = {Unsupervised adaptive image segmentation},
	booktitle = {ICASSP-95},
	year = {1995},
	note = {ScopusID: 0028996751doi: 10.1109/ICASSP.1995.479976},
	month = {1995///},
	pages = {2399 - 2402},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Piscataway},
	abstract = {This paper deals with the problem of unsupervised Bayesian segmentation of images modeled by Markov Random Fields (MRF). If the model parameters are known then we have various methods to solve the segmentation problem (Simulated Annealing, ICM, etc...). However, when they are not known, the problem becomes more difficult. One has to estimate the hidden label field parameters from the available image only. Our approach consists of a recent iterative method of estimation, called Iterative Conditional Estimation (ICE), applied to a monogrid Markovian image segmentation model. The method has been tested on synthetic and real satellite images.},
	author = {Zoltan Kato and Josiane Zerubia and Marc Berthod and Wojciech Pieczynski},
	editor = {*IEEE Signal Pro *Society}
}
