, REFERENCES

N. Giordana and W. Pieczynski, Estimation of generalized multisensor hidden Markov chains and unsupervised image segmentation, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.19, issue.5, pp.465-475, 1997.
DOI : 10.1109/34.589206

S. Geman and D. Geman, Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images, IEEE Trans. Pattern Anal. Mach. Intell, vol.6, pp.721-741, 1984.

J. Laferté, P. Pérez, and F. Heitz, Discrete Markov image modeling and inference on the quadtree, IEEE Transactions on Image Processing, vol.9, issue.3, pp.390-404, 2000.
DOI : 10.1109/83.826777

J. Provost, C. Collet, P. Rostaing, P. Pérez, and P. Bouthemy, Hierarchical Markovian segmentation of multispectral images for the reconstruction of water depth maps, Computer Vision and Image Understanding, vol.93, issue.2, pp.155-174, 2004.
DOI : 10.1016/j.cviu.2003.07.004

URL : https://hal.archives-ouvertes.fr/hal-00783668

J. Marroquin, S. Mitter, and T. Poggio, Probabilistic Solution of Ill-Posed Problems in Computational Vision, Journal of the American Statistical Association, vol.18, issue.397, pp.76-89, 1987.
DOI : 10.1109/TIT.1972.1054786

E. Monfrini and W. Pieczynski, Estimation de mélanges généralisés dans les arbres de Markov cachés, applicationàapplication`applicationà la segmentation des images de cartons d'orgue de barbarie, Traitement du Signal, vol.22, issue.2, 2005.

M. Mignotte, C. Collet, P. Pérez, P. Bouthemy-benboudjema, and W. Pieczynski, Sonar image segmentation using an unsupervised hierarchical MRF model Unsupervised statistical segmentation of nonstationary images using triplet Markov fields, IEEE Trans. Image Process. IEEE Trans. Pattern Anal. Mach. Intell, vol.9, issue.29 8, pp.1216-1231, 2000.
DOI : 10.1109/83.847834

URL : http://www.irisa.fr/vista/Papers/2000_ieeeip_mignotte.pdf

W. Pieczynski, Arbres de Markov Triplet et fusion de Dempster???Shafer, Comptes Rendus Mathematique, vol.336, issue.10, pp.869-872, 2003.
DOI : 10.1016/S1631-073X(03)00188-2

URL : https://hal.archives-ouvertes.fr/hal-01331300

W. Pieczynski, C. Hulard, and T. Veit, Triplet Markov chains in hidden signal restoration, International Symposium on Remote Sensing. International Society for Optics and Photonics, pp.58-68, 2003.
DOI : 10.1117/12.463183

J. Courbot, E. Monfrini, V. Mazet, and C. Collet, Oriented Triplet Markov Fields, Pattern Recognition Letters, 2018.
DOI : 10.1016/j.patrec.2017.12.026

URL : https://hal.archives-ouvertes.fr/hal-01744716

E. Monfrini, T. Ledru, E. Vaie, and W. Pieczynski, Segmentation non supervisée d'images par arbres de Markov cachés, 17ème Colloque GRETSI, 1999.

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.39-55, 1987.
DOI : 10.1109/TPAMI.1987.4767871

G. Celeux and J. Diebolt, L'algorithme SEM: un algorithme d'apprentissage probabiliste pour la reconnaissance de mélange de densités, Revue de statistique appliquée, pp.35-52, 1986.

A. P. Dempster, N. M. Laird, and D. B. Rubin, Maximum likelihood from incomplete data via the EM algorithm, J. R. Stat. Soc.. Series B, pp.1-38, 1977.