C. Lacoste, X. Descombes, and E. J. Zerubia, A comparative study of point processes for line network extraction in remote sensing, 2002.
URL : https://hal.archives-ouvertes.fr/inria-00072072

. C. Journaux-français-2, X. Lacoste, J. Descombes, E. N. Zerubia, and . Baghdadi, Extraction automatique des réseaux linéiqueslinéiquesà partir d'images satellitaires et aériennes par processus markov objet, Bulletin de la S.F.P.T, vol.170, pp.13-22, 2003.

. C. Journaux-internationaux-3, X. Lacoste, E. J. Descombes, and . Zerubia, Point Processes for Unsupervised Line Network Extraction in Remote Sensing, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2003.

. C. Conférences-francophones-avec-actes-4, X. Lacoste, J. Descombes, E. N. Zerubia, and . Baghdadi, Extraction de réseaux linéiqueslinéiquesà partir d'images satellitaires par processus Markov objet, 2003.

. C. Conférences-internationales-avec-actes-5, X. Lacoste, E. J. Descombes, and . Zerubia, Road network extraction in remote sensing by a Markov object process, Proceedings of IEEE ICIP, 2003.

X. Descombes, F. Kruggel, C. Lacoste, M. Ortner, G. Perrin et al., Marked point process in image analysis, Proceedings of 189
DOI : 10.1109/MSP.2002.1028354

C. Lacoste, X. Descombes, J. Zerubia, and E. N. Baghdadi, Bayesian geometric model for line network extraction from satellite images, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2004.
DOI : 10.1109/ICASSP.2004.1326607

C. Lacoste, X. Descombes, J. Zerubia, and E. N. Baghdadi, Unsupervised line network extraction from remotely sensed images by polyline process, Proceedings of EUSIPCO, 2004.

.. C. Séminaires-9, X. Lacoste, E. J. Descombes, and . Zerubia, A comparative study of point processes for line network extraction from images. Mini-Symposium in Stochastic Geometry, CWI, 2002.

C. Lacoste, X. Descombes, and E. J. Zerubia, Extraction du réseau linéique en télédétection par Processsus Markov Objet, BRGM, 2002.

C. Lacoste, X. Descombes, and E. J. Zerubia, Extraction du Réseau Linéique en Télédétection par Processsus Markov Objet, Séminaire Ariana -Mistral: " Stratégies stochastiques d'exploration d'´ etat appliquées au traitement d'image etàet`età la modélisation de réseaux, 2003.

C. Lacoste, X. Descombes, and E. J. Zerubia, Line network extraction in remote sensing by spatial processes, 2003.

C. Lacoste, X. Descombes, and E. J. Zerubia, CAROLINE: a CARtographic Oriented LIne Network Extraction model. Spatial Point Process Modelling and its Applications, 2004.

. Baddeley, ]. A. Van-lieshout, M. N. Baddeley, and . Van-lieshout, Stochastic geometry models in high-level vision, Journal of Applied Statistics, vol.55, issue.5-6, pp.233-258, 1993.
DOI : 10.1098/rsta.1990.0127

C. Barzohar, D. B. Barzohar, and . Cooper, Automatic finding of main roads in aerial images by using geometric-stochastic models and estimation, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.18, issue.7, pp.707-721, 1996.
DOI : 10.1109/34.506793

. Baumgartner, Update of roads in GIS from aerial imagery: verification and multiresolution extraction. International Archive of Photogrammetry and Remote Sensing, pp.3153-58, 1996.

. Baumgartner, Automatic road extraction based on multi-scale, grouping, and context, Photogrammetric Engineering and Remote Sensing, vol.65, issue.7, pp.777-785, 1999.

]. J. Besag, Statistical analysis of dirty pictures*, Journal of Applied Statistics, vol.6, issue.5-6, pp.259-302, 1986.
DOI : 10.1016/0031-3203(83)90012-2

]. U. Bhattacharya-et-parui, S. K. Bhattacharya, and . Parui, An improved backpropagation neural network for detection of road-like features in satellite imagery, International Journal of Remote Sensing, vol.18, issue.16, pp.3379-3394, 1997.
DOI : 10.1080/014311697216937

. Bicego, Automatic road extraction from aerial images by probabilistic contour tracking, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429), pp.585-588, 2003.
DOI : 10.1109/ICIP.2003.1247312

. Bobillet, Contours actifs : applicationàapplicationà la détection de rangs de cultures en télédétection haute résolution, 2003.

]. J. Bresenham, Algorithm for computer control of a digital plotter, Bibliographie 11. [Bresenham, pp.25-30, 1965.
DOI : 10.1147/sj.41.0025

]. J. Canny, A computational approach to edge detection, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.8, issue.6, pp.679-698, 1986.

C. Et-nicholls, ]. P. Clifford, and G. Nicholls, Comparison of birth-anddeath and Metropolis-Hastings Markov chain Monte Carlo for the Strauss process, 1994.

C. Et-ranchin, ]. I. Couloigner, and T. Ranchin, Mapping of urban areas: A multiresolution modeling approach for semi-automatic extraction of streets, Photogrammetric Engineering and Remote Sensing, vol.66, issue.7, pp.867-874, 2000.

]. R. Deriche, Using Canny's criteria to derive a recursively implemented optimal edge detector, International Journal of Computer Vision, vol.1, issue.2, pp.167-187, 1987.
DOI : 10.1007/BF00123164

. Descombes, Fine structure preserving Markov model for image processing, 9th Scandinavian Conference on Image Analysis, pp.349-356, 1995.

]. I. Destival, Recherche automatique des réseaux linéaires sur les images SPOT, Bulletin de la S.F.P.T, vol.105, pp.5-16, 1987.

D. Et-desachy, ]. P. Dhérété, and J. Desachy, Data fusion for linear geographic feature matching on SPOT images, Bulletin de la S.F.P.T, vol.153, pp.88-90, 1999.

. Doucette, Self-organised clustering for road extraction in classified imagery, ISPRS Journal of Photogrammetry and Remote Sensing, vol.55, issue.5-6, pp.347-358, 2001.
DOI : 10.1016/S0924-2716(01)00027-2

H. O. Duda, P. Duda, and . Hart, Pattern Classification and Scene Analysis, 1973.

. Eberly, Ridges for image analysis, Journal of Mathematical Imaging and Vision, vol.1672, issue.4, pp.353-373, 1994.
DOI : 10.1007/BF01262402

. Fischler, Detection of roads and linear structures in low-resolution aerial imagery using a multisource knowledge integration technique, Computer Graphics and Image Processing, vol.15, issue.3, pp.201-223, 1981.
DOI : 10.1016/0146-664X(81)90056-3

. Fua, ]. P. Leclerc, Y. G. Fua, and . Leclerc, Model driven edge detection. Machine Vision and Applications, pp.45-56, 1990.

. Garcin, Building detection by Markov object processes and a MCMC algorithm Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.6, pp.721-741, 1984.

G. Et-jedynak, ]. D. Geman, and B. Jedynak, An active testing model for tracking roads in satellite images, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.18, pp.1-14, 1996.

]. T. Géraud, Fast Road Network Extraction in Satellite Images Using Mathematical Morphology and Markov Random Fields, Nonlinear Signal and Image Processing, 2003.
DOI : 10.1155/S1110865704409093

]. C. Geyer-et-møller, J. Geyer, and . Møller, Simulation and likelihood inference for spatial point process, Scandinavian Journal of Statistics, Series B, vol.21, pp.359-373, 1994.

]. C. Geyer, Stochastic Geometry: Likelihood and Computation, chapitre 3, pp.79-140, 1999.

]. P. Green, Reversible jump Markov chain Monte Carlo computation and Bayesian model determination, Biometrika, vol.82, issue.4, pp.97-109, 1995.
DOI : 10.1093/biomet/82.4.711

L. Grün, H. Grün, and . Li, Road extraction from aerial and satellite images by dynamic programming, ISPRS Journal of Photogrammetry and Remote Sensing, vol.50, issue.4, pp.11-20, 1995.
DOI : 10.1016/0924-2716(95)98233-P

. Guigues, ]. L. Vilgino, J. Guigues, and . Vilgino, Automatic road extraction through light propagation simulation. International Archive of Photogrammetry and Remote Sensing, volume XXXIII, 2000.

]. C. Gurney, Threshold Selection for Line Detection Algorithms, IEEE Transactions on Geoscience and Remote Sensing, vol.18, issue.2, pp.4-211, 1980.
DOI : 10.1109/TGRS.1980.350274

]. W. Harvey, Performance evaluation for road extraction, Bulletin de la S.F.P.T, vol.153, pp.79-87, 1999.

]. W. Hastings, Monte Carlo sampling methods using Markov chains and their applications, Biometrika, vol.57, issue.1, pp.97-109, 1970.
DOI : 10.1093/biomet/57.1.97

]. D. Haverkamp, Extracting straight road structure in urban environments using IKONOS satellite imagery, Optical Engineering, vol.41, issue.9, pp.2107-2110, 2002.
DOI : 10.1117/1.1496785

. Heipke, A hierarchical approach to automatic road extraction from aerial imagery Integrating Photogrammetric Techniques with Scene Analysis and Machine Vision II, Proc. SPIE, pp.222-231, 1995.

. Hivernat, Qualification automatique des résultats d'une mise en correspondance de réseaux routiers en vue de la misè a jour cartographique, Bulletin de la S.F.P.T, vol.153, pp.91-93, 1999.

. Hoffmann, Concepts in optimizing simulated annealing schedules: an adaptive approach for parallel and vector machines. M. Grauer et D.B. Pressmar, ´ editeurs, Parallel and Distributed Optimization, Bibliographie, vol.39, 1991.

L. Huber, K. Huber, and . Lang, Road extraction from high-resolution airborne SAR using operator fusion, IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217), 2001.
DOI : 10.1109/IGARSS.2001.978172

]. M. Imberty and X. Descombes, Simulation de processus objets : Etude de faisabilité pour une applicationàapplicationà la segmentation d'images, 2000.

K. Et-møller, ]. W. Kendall, and J. Møller, Perfect Metropolis-Hastings simulation of locally stable spatial point processes, Advances in Applied Probability, vol.32, pp.844-865, 2000.

. Kerstan, Infinitely divisible point processes, 1978.

. Koller, Multiscale detection of curvilinear structures in 2-D and 3-D image data, Proceedings of IEEE International Conference on Computer Vision, pp.864-869, 1995.
DOI : 10.1109/ICCV.1995.466846

. Lacoste, A comparative study of point processes for line network extraction in remote sensing, 2002.
URL : https://hal.archives-ouvertes.fr/inria-00072072

. Laptev, Automatic extraction of roads from aerial images based on scale space and snakes, Machine Vision and Applications, pp.23-31, 2000.
DOI : 10.1007/s001380050121

]. T. Lindeberg, Edge detection and ridge detection with automatic scale selection, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.77-116, 1998.
DOI : 10.1109/CVPR.1996.517113

M. Et-zerubia, ]. N. Merlet, and J. Zerubia, New prospects in line detection by dynamic programming, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.18, issue.4, pp.426-431, 1996.

. Metropolis, Equation of State Calculations by Fast Computing Machines, The Journal of Chemical Physics, vol.21, issue.6, pp.1087-1092, 1953.
DOI : 10.1063/1.1699114

. Neuenschwander, Ziplock snakes, International Journal of Computer Vision, vol.25, issue.3, pp.191-201, 1997.
DOI : 10.1023/A:1007924018415

]. M. Ortner, D. , I. , S. Antipolis, and . France, Extraction de caricatures de bâtiments sur des modèles numériques d'´ elévation Jetstream: probabilistic contour extraction with particles, Proceedings of IEEE Int. Conf. on Computer Vision, volume II, pp.524-531, 2001.

. Perrin, Tree crown extraction using marked point processes, Proceedings of EUSIPCO, 2004.
URL : https://hal.archives-ouvertes.fr/tel-00109074

]. P. Peskun, Optimum Monte-Carlo sampling using Markov chains, Biometrika, vol.60, issue.3, pp.607-612, 1973.
DOI : 10.1093/biomet/60.3.607

. Péteri, A multiresolution modelling approach for semi-automatic extraction of streets: application to high resolution images from the Ikonos satellite Observing our environment from space: new solutions for a new millenium, Proceedings of the EARSeL/SFPT Symposium, 2001.

V. Poli, G. Poli, and . Valli, An algorithm for real-time vessel enhancement and detection, Computer Methods and Programs in Biomedicine, vol.52, issue.1, pp.1-22, 1996.
DOI : 10.1016/S0169-2607(96)01773-7

]. C. Preston, Spatial birth and death processes, Advances in Applied Probability, vol.7, issue.03, pp.371-391, 1976.
DOI : 10.1016/0001-8708(70)90034-4

. Rellier, Local registration and deformation of a road cartographic database on a SPOT satellite image, Pattern Recognition, vol.35, issue.10, pp.2213-2222, 2002.
DOI : 10.1016/S0031-3203(01)00180-7
URL : https://hal.archives-ouvertes.fr/inria-00072711

]. B. Ripley, Modelling spatial patterns, Journal of the Royal Statistical Institute, Series B, vol.39, pp.172-212, 1977.

R. Et-casella, ]. C. Robert, and G. Casella, Monte Carlo Statistical Methods , chapitre 8, 1999.

]. C. Robert, Méthodes de Monte Carlo par cha??nescha??nes de Markov. Statistique mathématique et probabilité, Economica, 1996.

. Rochery, Contours actifs d'ordre supérieur appliquésappliquésà la détection de linéiques dans des images de télédétection, 2003.

]. L. Roux, Recalage d'images multi-sources. Application au recalage d'une image SPOT et d'une carte, Thèse de Doctorat, ENST, 1992.

]. D. Ruelle, Superstable interactions in classical statistical mechanics, Communications in Mathematical Physics, vol.87, issue.2, pp.127-159, 1970.
DOI : 10.1007/BF01646091

]. R. Ruskoné, Extraction automatique du réseau routier par interprétation locale du contexte, Thèse de Doctorat, 1996.

]. Sampère, Evaluation de l'utilisation de données supermode SPOT5 pour la misè a jour de BD IGN, Bulletin de la S.F.P.T, vol.164, pp.96-105, 2001.

[. S. Hinz, ]. S. Baumgartner, A. Hinz, and . Baumgartner, Automatic extraction of urban road networks from multi-view aerial imagery, ISPRS Journal of Photogrammetry and Remote Sensing, vol.58, issue.1-2, pp.83-98, 2003.
DOI : 10.1016/S0924-2716(03)00019-4

]. C. Steger, Extracting curvilinear structures: A differential geometric approach, Proceedings of European Conf. on Computer Vision, pp.630-641, 1996.
DOI : 10.1007/BFb0015573

]. C. Steger, An unbiased detector of curvilinear structures, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.20, issue.2, pp.113-125, 1998.
DOI : 10.1109/34.659930

. Stoica, A Gibbs Point Process for Road Extraction from Remotely Sensed Images, International Journal of Computer Vision, vol.57, issue.2, pp.121-136, 2004.
DOI : 10.1023/B:VISI.0000013086.45688.5d

]. R. Stoica, Processus ponctuels pour l'extraction des réseaux linéiques dans les images satellitaires et aériennes, Thèse de Doctorat, 2001.

. Stoyan, Stochastic Geometry and Its Applications., Biometrics, vol.45, issue.2, 1987.
DOI : 10.2307/2531521

. Tupin, Detection of linear features in SAR images: application to road network extraction, IEEE Transactions on Geoscience and Remote Sensing, vol.36, issue.2, pp.434-453, 1998.
DOI : 10.1109/36.662728

. Urago, A Markovian model for contour grouping, 1994.
URL : https://hal.archives-ouvertes.fr/inria-00074550

L. Van, ]. M. Stoica, R. S. Van-lieshout, and . Stoica, The Candy model revisited: Markov properties and inference, 2001.

]. M. Van-lieshout and . Van-lieshout, Stochastic annealing for nearestneighbour point processes with application to object recognition. Rapport de Recherche BS-R9306, CWI, 1993.

. Vermaak, Variational inference for visual tracking, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings., 2003.
DOI : 10.1109/CVPR.2003.1211431

]. G. Vosselman-et-de-knecht, J. Vosselman, and . De-knechtwang, Road tracing by profile matching and Kalman filtering Automatic Extraction of Man-Made Objects from Aerial and Space Images Extraction du réseau routier urbainàurbainà l'aide d'images SPOT HRV, International Journal of Remote Sensing, vol.82, issue.174, pp.265-274827, 1995.

W. Et-pavlidis, ]. L. Wang, and T. Pavlidis, Detection of curved and straight segments from gray scale topography, CVGIP : Image Understanding, vol.58, issue.3, pp.352-365, 1993.

]. G. Winkler, Image Analysis, Random Fields and Markov Chain Monte Carlo Methods: a Mathematical Introduction, 2003.
DOI : 10.1007/978-3-642-55760-6

. Zhang, Road network detection by mathematical morphology, Bulletin de la S.F.P.T, vol.153, pp.94-96, 1999.

Z. Et-carnine, ]. A. Zlotnick, and P. Carnine, Finding road seeds in aerial images, Computer Vision, Graphics, and Image Processing, vol.57, pp.243-260, 1993.

. Cette-thèse-aborde-leprobì-eme-de-l, extraction non supervisée des réseaux linéiques (routes, rivì eres, etc.) ` a partir d'images satellitaires et aériennes. Nous utilisons des processus objet, ou processus ponctuels marqués, comme modèles a priori. Ces modèles permettent de bénéficier de l'apport d'un cadre stochastique (robustesse au bruit, corpus algorithmique, etc.) tout en manipulant des contraintes géométriques fortes

M. Carlo-par-cha??necha??ne-de-markov, Nous proposons tout d'abord une modélisation du réseau linéique par un processus dont les objets sont des segments interagissant entre eux Le modèle a priori est construit de façon façonà exploiter au mieux la topologie du réseau recherché au travers de potentiels fondés sur la qualité de chaque interaction. Les propriétés radiométriques sont prises en compte dans un terme d'attache aux données fondé sur des mesures statistiques. NousétendonsNousétendons ensuite cette modélisationmodélisationà des objets plus complexes. La manipulation de lignes brisées permet une extraction plus précise du réseau et améliore la détection des bifurcations. Enfin, nous proposons une modélisation hiérarchique des réseaux hydrographiques dans laquelle les affluents d'un fleuve sont modélisés par un processus de lignes brisées dans le voisinage de ce fleuve

. Mots-clés, Géométrie stochastique, processus ponctuels marqués, recuit simulé, MCMCàMCMCà sauts réversibles, extraction de réseaux linéiques