K. Abend, T. Harley, and L. N. , Classification of binary random patterns, IEEE Transactions on Information Theory, vol.11, issue.4, pp.538-544, 1965.
DOI : 10.1109/TIT.1965.1053827

M. Bello, A combined Markov random field and wave-packet transform-based approach for image segmentation, IEEE Transactions on Image Processing, vol.3, issue.6, pp.6-6, 1994.
DOI : 10.1109/83.336251

C. Bouman and M. Shapiro, A multiscale random field model for Bayesian image segmentation, IEEE Transactions on Image Processing, vol.3, issue.2, pp.162-177, 1994.
DOI : 10.1109/83.277898

Y. Boykov and V. Kolmogorov, An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision, Pattern Analysis and Machine Intelligence IEEE Transactions on, vol.26, pp.9-9, 2004.

Y. Boykov, O. Veksler, and R. Zabih, Fast approximate energy minimization via graph cuts, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.23, issue.11, pp.1222-1239, 2001.
DOI : 10.1109/34.969114

H. Derin and H. Elliott, Modeling and Segmentation of Noisy and Textured Images Using Gibbs Random Fields, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.9, issue.1, pp.1-1, 1987.
DOI : 10.1109/TPAMI.1987.4767871

D. M. Greig, B. Porteous, and A. Seheult, Exact Maximum A Posteriori Estimation for Binary Images, Journal of the Royal Statistical Society B, vol.51, pp.2-2, 1989.

R. Fjortoft, Y. Delignon, W. Pieczynski, M. Sigelle, and F. Tupin, Unsupervised classification of radar images using hidden Markov chains and hidden Markov random fields, IEEE Transactions on Geoscience and Remote Sensing, vol.41, issue.3, pp.3-3, 2003.
DOI : 10.1109/TGRS.2003.809940

URL : https://hal.archives-ouvertes.fr/hal-01347239

S. Geman and D. Geman, Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.6, issue.11, pp.6-6, 1984.

. G. Jr, The Viterbi Algorithm, Proceedings of the IEEE, pp.268-278, 1973.

Z. Kato, M. Berthod, and J. Zerubia, A Hierarchical Markov Random Field Model and Multitemperature Annealing for Parallel Image Classification, Graphical Models and Image Processing, vol.58, issue.1, pp.1-1, 1996.
DOI : 10.1006/gmip.1996.0002

URL : https://hal.archives-ouvertes.fr/inria-00074736

V. Kolmogorov and R. Zabih, What Energy functions can be Minimized via Graph Cuts?, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.26, pp.2-2, 2004.

F. Kschischang, B. Frey, and H. Loeliger, Factor graphs and the sum-product algorithm, IEEE Transactions on Information Theory, vol.47, issue.2, pp.2-2, 2001.
DOI : 10.1109/18.910572

S. Kuo and O. Agazzi, Keyword Spotting in Poorly Printed Documents Using Pseudo 2-D Hidden Markov Models, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.16, pp.8-8, 1994.

J. Laferte, P. Perez, and F. Heitz, Discrete Markov image modelling and inference on the quad tree, IEEE Transactions on Image Processing, vol.9, pp.3-3, 2000.

E. Levin and R. Pieraccini, Dynamic planar warping for optical character recognition, [Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing, pp.149-152, 1992.
DOI : 10.1109/ICASSP.1992.226254

M. Mignotte, C. Collet, P. Perez, and P. Bouthemy, Sonar image segmentation using an unsupervised hierarchical MRF model, IEEE Transactions on Image Processing, vol.9, issue.7, pp.1216-1231, 2000.
DOI : 10.1109/83.847834

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.37.8457

K. Murphy, Y. Weiss, and M. I. Jordan, Loopy belief-propagation for approximate inference: An empirical study, Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence, pp.467-475, 1999.

J. Pearl, Probabilistic Reasoning in Intelligent Systems, 1988.

W. Pieczynski, Convergence of the Iterative Conditional Estimation and Application to Mixture Proportion Identification, 2007 IEEE/SP 14th Workshop on Statistical Signal Processing, pp.49-53, 2007.
DOI : 10.1109/SSP.2007.4301216

A. Viterbi, Error bounds for convolutional codes and an asymptotically optimal decoding algorithm, IEEE Transactions on Information Theory, issue.13, pp.260-269, 1967.