J. [. Adelson and . Bergen, Spatiotemporal energy models for the perception of motion, Journal of the Optical Society of America A, vol.2, issue.2, pp.284-299, 1985.
DOI : 10.1364/JOSAA.2.000284

]. P. Abr97 and . Abry, Analyse continue par ondelettes, Diderot Sciences en Actes, 1997.

R. [. Antoine and . Murenzi, Two-dimensional directional wavelets and the scale-angle representation, Signal Processing, vol.52, issue.3, pp.259-281, 1996.
DOI : 10.1016/0165-1684(96)00065-5

R. [. Antoine and . Murenzi, Galilean wavelets: Coherent states of the affine Galilei group, Journal of Mathematical Physics, vol.40, issue.11, 1998.
DOI : 10.1063/1.533064

]. S. Amb00 and . Ambellouis, Analyse du mouvement dans les séquences d'images par une méthode récursive de filtrage spatio-temporel sélectif, 2000.

]. I. Amo04 and . Amonou, Thèse : Décompositions Hiérarchiques Non-Redondantes Orientées Régions pour le Codage des Images Numériques. Ecole doctorale d'informatique, télécommunications et electronique de paris ; spécialité signal et images, 2004.

R. [. Antoine, P. Murenzi, and . Vandergheynst, Directional Wavelets Revisited: Cauchy Wavelets and Symmetry Detection in Patterns, Applied and Computational Harmonic Analysis, vol.6, issue.3, pp.314-345, 1999.
DOI : 10.1006/acha.1998.0255

URL : http://doi.org/10.1006/acha.1998.0255

J. P. Antoine, R. Murenzi, P. Vandergeynst, and J. P. Ali, 2D CWT Wavelets, 2004.

]. K. And02 and . Andersson, Quality and Motion Estimation for Image Sequence Coding, 2002.

]. E. Bac03 and . Bacry, LastWave Manual and C-Code. CMAP, Centre de mathématiques appliquées, 2003.

]. M. Bal98 and . Balsi, Focal-plane optical flow computation by foveated CNNs, Proc. of Fifth IEEE International Workshop on Cellular Neural Networks and their Applications (CNNA-98), pp.149-154, 1998.

J. [. Beauchemin, B. D. Barron, G. Borshukov, Y. Bozdagi, A. M. Altunbasak et al., The Fourier properties of discontinuous motion Motion Segmentation by Multistage Affine Clasification, IEEE Transactions on Image Processing, vol.6, issue.14711, pp.1591-1594, 1997.

]. C. Ber99a and . Bernard, Discrete wavelet analysis for fast optic flow computation, Rapport Interne du Centre de Mathématiques Appliquées RI415, Ecole Polytechnique, CMAP, Centre de Mathématiques Appliquées, 1999.

]. C. Ber99b and . Bernard, Thèse : Ondelettes etprobì emes mal posés : la mesure du flot optique et l'interpolationirrégulì ere, 1999.

]. G. Bey92 and . Beylkin, On the representation of operators in bases of compactly supported wavelets, SIAM J. on Numerical Analysis, vol.6, issue.29, pp.1716-1740, 1992.

R. [. Bouthemy and . Fablet, Motion characterization from temporal cooccurrences of local motion-based measures for video indexing, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170), 1998.
DOI : 10.1109/ICPR.1998.711298

D. [. Barron, S. S. Fleet, and . Beauchemin, Performance of optical flow techniques, International Journal of Computer Vision, vol.54, issue.1, pp.43-77, 1994.
DOI : 10.1007/BF01420984

. [. Burke-hubbard, Ondes et ondelettes. La saga d'un outil mathématique. Belin, collection " pour la science, 1995.

I. [. Bereziat, L. Herlin, and . Younes, A generalized optical flow constraint and its physical interpretation, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662), 2000.
DOI : 10.1109/CVPR.2000.854890

URL : https://hal.archives-ouvertes.fr/inria-00532741

R. [. Berkner and . Wells-jr, A fast approximation to the continuous wavelet transform with applications, Conference Record of the Thirty-First Asilomar Conference on Signals, Systems and Computers (Cat. No.97CB36136), 1997.
DOI : 10.1109/ACSSC.1997.679101

C. [. Bonnaud and K. J. Labit, Interpolative coding of image sequences using temporal linking of motion-based segmentation, 1995 International Conference on Acoustics, Speech, and Signal Processing, 1995.
DOI : 10.1109/ICASSP.1995.479942

]. P. Bm01a, H. Brault, and . Mounier, Automated, transformation invariant, shape recognition through wavelet multiresolution, Proceedings of the SPIE, International Society for Optical Engineering Wavelets : Applications in Signal and Image Processing IX, pp.434-443, 2001.

]. P. Bm01b, H. Brault, and . Mounier, Wavelet multi-resolution transform applied to shape recognition based on a curvature criterion, Proceedings of the IAPR International Conference on Image and Signal Processing, 2001.

]. P. Bra03a and . Brault, Motion estimation and video compression with spatio-temporal motiontuned wavelets, WSEAS Transactions on Mathematics, vol.2, issue.1 2, pp.67-78, 2003.

]. P. Bra03b and . Brault, A new scheme for object-oriented video compression and scene analysis, based on motion tuned spatio-temporal wavelet family and trajectory identification, Proceedings of the 3rd IEEE International Symposium on Signal Processing and Information Technology, 2003.

]. P. Bra04 and . Brault, On the performances and improvements of motion-tuned wavelets for motion estimation, WSEAS Transactions on Electronics, vol.1, issue.1, pp.174-180, 2004.

]. W. Bri87, . Briggs, . J. Brs-+-94-]-t, R. Burns, S. K. et al., Discrete, spatiotemporal, wavelet multiresolution analysis method for computing optical flow Characterization of nanostructures stm images with the wavelet and ridgelet transforms Wavelet interpolation networks for hierarchical approximation Motion-compensated spatio-temporal filtering with wavelets Ridgelets : Theory and Applications Harmonic analysis of neural networks Ridgelets : Estimating with ridge functions Dynamic motion analysis using wavelet flow surface images Centre-frequency adaptive IIR temporal filters for phase-based image velocity estimation Analysis of deformational transformations with spatio-temporal continuous wavelet transforms Simultaneous motion estimation and segmentation, Proceedings of the IAPR International Conference on Image and Signal Processing Proc. of SPIE's 44th Annual MeetingCHA03] P. Carre, D. Helbert, and E. Andres. 3d fast ridgelet transform. Proceedings of ICIP Proceedings of IEEE-ICASSPCP03] N. Cammas and S. Pateux. Codage video scalable par maillage et ondelettes 3d Proceedings of CORESA, 2003. [CTS97] M. M. Chang, A. M. Tekalp, and M. I. SezanCVZ98] B. Chai, J. Vass, and X. Zhuang. Statistically adaptive wavelet image codingDBB91] J.N. Driessen, L. Boroczky, and J. Biemond. Pel-recursive motion field estimation from image sequences. Journal of Visual Communication and Image ReproductionDC98] F. De Coulon. Théorie et traitement des signaux, pp.2236-22471131, 1987.

B. Duval-destin, R. A. Murenzidir58-]-p, . [. Dirac, P. Deriche, G. Kornprobst et al., Frontì eres Un soupçon de théorie des groupes : groupe des rotations et groupe de Poincaré The Principles of Quantum Mechanics. The international series and monographs on physics 27 Optical-flow estimation while preserving its discontinuities : A variational approach Segmentation-based motion estimation for second generation video coding techniques Spatio-temporal segmentation based on motion and static segmentation Morris, and Zerubia. Quelques améliorationsaméliorationsà la segmentation d'images bayésiennes Estimation of markov random field prior parameters using markov chain monte carlo maximum likelihood Factoring wavelet transforms into lifting steps, Progress in Wavelet Analysis and Applications Proc. Second Asian Conf. Computer Vision,ACCV MIT, Media Lab. and Swiss FIT, S.P. LabDS98] I. Daubechies and W. SweldensDut89] P. Dutilleux. Wavelets Time-Frequency Methods and Phase Space, chapter an Implementation of the algorithme a trous to compute the wavelet transform, pp.399408-290, 1958.

]. W. Springer-verlagfa91, E. H. Freeman, ]. J. Adelsonfey79, A. D. Fleet, and . Jepson, The design and use of steerable filters Le cours de physique de Feynman : Mécanique Quantique. InterEditions, edition originale : the feynman lectures on physics Computation of component image velocity from local phase information, 1990. [FSR03] M. Fliess and Hebertt Sira-Ramirez. An algebraic framework for linear identification. In ESAIM Contr. Opt. Calc. Variat, pp.891-90677, 1965.

A. Grossman, R. Kronland-martinet, and J. Morlet, Wavelets Time-Frequency Methods and Phase Space, Proceedings of the International Conference of Marseille, dec. 87, chapter Introduction to Wavelet Transforms, pp.2-20

]. A. Gui94 and . Guichardet, Majeure de mathématiques. Groupes de Lie, représentations, 1994.

N. [. Hong, M. Cui, S. Pronobis, and . Scott, Local motion feature aided ground moving target tracking with GMTI and HRR measurements, IEEE Transactions on Automatic Control, vol.50, issue.1, pp.127-133, 2005.
DOI : 10.1109/TAC.2004.841119

]. D. Hee87 and . Heeger, Optical flow using spatiotemporal filters, International Journal of Computer Vision, vol.1, pp.279-302, 1987.

M. Holschneider, R. Kronland-martinet, J. Morlet, and P. Tchamitchian, Thè a trous algorithm, CPT-88/P.2215, pp.1-22, 1988.

B. [. Horn and . Schunck, Determining optical flow, Artificial Intelligence, vol.17, issue.1-3, pp.185-204, 1981.
DOI : 10.1016/0004-3702(81)90024-2

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.185.1651

M. [. Jehan-besson, G. Barlaud, and . Aubert, Segmentation et suivi des objets en mouvement dans une séquence vidéo par contours actifs basés régions, Procesdings of CORESA, 2000.

[. Konrad and E. Dubois, Bayesian estimation of motion vector fields, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.14, issue.9, pp.910-927, 1992.
DOI : 10.1109/34.161350

. P. Lck-+-98-]-j, J. Leduc, M. Corbett, V. M. Kong, B. K. Wickerhauser et al., Accelerated spatio-temporal wavelet transforms : An iterative trajectory estimation, Proceedings of ICASSP, pp.2777-2780, 1998.

]. J. Led94 and . Leduc, Digital Moving Pictures, volume 3 of Advances in Image Communication, 1994.

]. J. Led97 and . Leduc, Spatio-temporal wavelet transforms for digital signal analysis, Signal Processing, vol.60, pp.23-41, 1997.

]. C. Lee04 and . Lee, Joint source-Channel Coding Tools for Robust Transmission of Video Sequences ; Application to H.263+ and H.264, 2004.

T. [. Liu, M. Hong, R. Herman, and . Chellappa, Accuracy vs efficiency trade-offs in optical flow algorithms, Proceedings of European Conference on Computer Vision, volume II, pp.174-183, 1996.

T. [. Lucas and . Kanade, An iterative image registration technique with an application to stereo vision, Proceedgins of DARPA Image Understanding Worshop, pp.121-130, 1981.

. [. Levy-leblond, Galilei group and non-relativistic quantum mechanics, Journal of mathematical physics, vol.4, issue.6, 1963.

[. Leduc, F. Mujica, R. Murenzi, and M. J. Smith, Spatio-temporal wavelet transforms for motion tracking, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing, pp.3013-3016, 1997.
DOI : 10.1109/ICASSP.1997.595426

B. P. Leduc, F. Mujica, R. Murenzi, and M. J. Smith, Spatiotemporal wavelets : A group-theoretic construction for motion estimation and tracking, Siam Journal of Applied Mathematics, issue.2, pp.61596-632, 2000.

[. Leduc, J. Odobez, and C. Labit, Adaptive motion-compensated wavelet filtering for image sequence coding, IEEE Transactions on Image Processing, vol.6, issue.6, pp.862-878, 1997.
DOI : 10.1109/83.585236

[. Pennec, Bandelettes et représentation géometrique des images, 2002.

[. Pennec and S. Mallat, Image compression with geometrical wavelets, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101), 2000.
DOI : 10.1109/ICIP.2000.901045

[. Pennec and S. Mallat, Représentation d'image par bandelettes et applicationà applicationà la compression Proceeedings of GRETSI New fast algorithms for the estimation of block motion vectors, IEEE Transactions on Circuits, Systems and Video Technology, vol.3, pp.148-157, 1993.

M. [. Mahmoud, R. J. Afifi, and . Green, Recognition and velocity computation of large moving objects in images, ICASSP, pp.1790-1791, 1988.
DOI : 10.1109/29.9020

]. S. Mal89 and . Mallat, A theory for multiresolution signal decomposition, IEEE Transactions on PAMI, vol.11, pp.167-180, 1989.

]. S. Mal00 and . Mallat, Majeure de mathématiques appliquées : traitement du signal. CMAP, Département de mathématiques appliquées, 2000.

]. S. Mal01 and . Mallat, A Wavelet Tour of Signal Processing, 1997.

]. F. Mb94a, P. Meyer, and . Bouthemy, Region-based tracking using affine motion models in long image sequences, CVGIP : Image Understanding, vol.60, issue.2, pp.119-140, 1994.

]. D. Mb94b, A. Murray, and . Basu, Motion tracking with an active camera, IEEE PAMI, vol.16, pp.449-459, 1994.

M. K. Mandal, E. Chan, X. Wang, and S. Panchanathan, Multiresolution motion estimation techniques for video compression, Optical Engineering, vol.35, issue.1, pp.128-136, 1996.
DOI : 10.1117/1.600883

F. [. Moscheni, M. Dufaux, and . Kunt, A new two-stage global/local motion estimation based on a background/foreground segmentation, 1995 International Conference on Acoustics, Speech, and Signal Processing, 1995.
DOI : 10.1109/ICASSP.1995.479941

W. [. Mallat and . Hwang, Singularity detection and processing with wavelets, IEEE Transactions on Information Theory, vol.38, issue.2, pp.617-643, 1992.
DOI : 10.1109/18.119727

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.36.5153

D. Marpe, G. Heising, H. L. Cycon, and A. Petukhov, Wavelet-based video coding using image warping and overlapped block motion compensation, IEEE transactions on Circuits and Systems for Video Technology, 2000.

N. [. Magarey and . Kingsbury, An improved motion estimation algorithm using complex wavelets, Proceedings of 3rd IEEE International Conference on Image Processing, pp.969-972, 1996.
DOI : 10.1109/ICIP.1996.559662

N. [. Magarey and . Kingsbury, Motion estimation using a complex-valued wavelet transform, IEEE Transactions on Signal Processing, vol.46, issue.4, pp.1069-1084, 1998.
DOI : 10.1109/78.668557

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.56.8705

J. [. Mujica, R. Leduc, M. J. Murenzi, and . Smith, Spatio-temporal continuous wavelets applied to missile warhead detection and tracking, pp.787-798, 1997.

J. [. Mujica, R. Leduc, M. Murenzi, and . Smith, A new motion parameter estimation algorithm based on the continuous wavelet transform, IEEE Transactions on Image Processing, vol.9, issue.5, pp.873-888, 2000.
DOI : 10.1109/83.841533

]. F. Mor98 and . Morier, Méthodes de Représentation Hiérarchique du Contenu des Séquences d'Images Animées, 1998.

]. E. Mp98a, P. Memin, and . Perez, Dense estimation and object-based segmentation of the optical flow with robust techniques, IEEE Transactions on Image Processing, vol.7, issue.5, pp.703-719, 1998.

]. E. Mp98b, P. Memin, and . Perez, A multigrid approach for hierarchical motion estimation, Proceedings of International Conference on Computer Vision, pp.933-938, 1998.

]. J. Msb97a, E. Mendelsohn, R. Simoncelli, and . Bajcsy, Discrete-time rigidity-constrained optical flow, Seventh International Conference on Computer Analysis of Images and Patterns, 1997.

]. J. Msb97b, E. Mendelsohn, R. Simoncelli, and . Bajcsy, Discrete-time rigidity-constrained optical flow assuming planar structure, GRASP laboratory technical report, 1997.

T. [. Marpe, H. L. Wiegand, and . Cycon, Design of a highly efficient wavelet-based video coding scheme, Visual Communications and Image Processing 2002, 2002.
DOI : 10.1117/12.453041

S. [. Mallat and . Zhong, Characterization of signals from multiscale edges, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.14, issue.7, 1992.

P. [. Odobez and . Bouthemy, Direct incremental model-based image motion segmentation for video analysis, Signal Processing, vol.66, issue.2, pp.143-155, 1998.
DOI : 10.1016/S0165-1684(98)00003-6

E. [. Oisel, L. Mémin, C. Morin, and . Labit, Epipolar constrained motion estimation for reconstruction from video sequences, Spie Conf. on Visual Communications and Image Processing, 1998.

O. [. Papadopoulo and . Faugeras, Analyse du mouvement tridimensionneì a partir de séquences d'images en utilisant des surfaces Rapport n 2167, programme 4 (robotique, image et vision, projet robotvis, INRIA, 1994.

H. [. Park and . Kim, Motion estimation using low-band shift method for waveletbased moving picture coding, IEEE transactions on image processing, 2000.

B. Pesquet-popescu and V. Bottreau, Three-dimensional lifting schemes for motion compensated video compression, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221), pp.7-11, 2001.
DOI : 10.1109/ICASSP.2001.941289

]. G. Que01 and . Quenot, Computation of optical flow using dynamic programming, 2001.

E. [. Starck, D. L. Candes, and . Donoho, Image restoration by the curvelet transform, Proceedings of ICISP, Int'l Conference on Image and Signal Processing, 2001.

]. J. Sha93 and . Shapiro, Embedded image coding using zerotrees of wavelet coefficients, IEEETSP, issue.12, pp.413445-3462, 1993.

]. M. She92 and . Shensa, The discrete wavelet transform : Wedding thè a trous and mallat algorithm, IEEE Transactions on signal processing, vol.40, issue.10, pp.2464-2482, 1992.

]. E. Sim98 and . Simoncelli, Handbook of computer vision and applications, chapter Bayesian multiscale differential optical flow, 1998.

F. [. Starck, A. Murtagh, and . Bijaoui, Image Processing and Data Analysis ; the multiscale approach, 1998.

W. [. Said and . Pearlman, A new, fast, and efficient image codec based on set partitioning in hierarchical trees, IEEE Transactions on Circuits and Systems for Video Technology, vol.6, issue.3, pp.243-250, 1996.
DOI : 10.1109/76.499834

K. [. Sukmarg and . Rao, Fast object detection and segmentation in MPEG compressed domain, 2000 TENCON Proceedings. Intelligent Systems and Technologies for the New Millennium (Cat. No.00CH37119), 2000.
DOI : 10.1109/TENCON.2000.892290

K. [. Shah, P. S. Rangarajan, and . Tsai, Motion trajectories, IEEE Transactions on Systems, Man, and Cybernetics, vol.23, issue.4, pp.1138-1150, 1993.
DOI : 10.1109/21.247894

D. [. Secker and . Taubman, Motion-compensated highly scalable video compression using an adaptative 3d wavelet transform based on lifting, 2001.

]. W. Swe95 and . Sweldens, The Construction and Application of Wavelets in Numerical Analysis, 1995.

]. D. Tau00 and . Taubman, High performance scalable image compression with ebcot, IEEE Transactions on Image Processing, vol.9, issue.7, pp.1158-1170, 2000.

C. [. Tziritas and . Labit, Motion Analysis for Image Sequence Coding, of Advances in Image Communication, 1994.

]. B. Tor95 and . Torresani, Analyse continue par ondelettes. Savoirs actuels, CNRS Editions, 1995.

]. F. Tru98 and . Truchetet, Ondelettes pour le signal numérique, Hermes, 1998.

A. [. Taubman and . Zakhor, Multirate 3-D subband coding of video, IEEE Transactions on Image Processing, vol.3, issue.5, pp.572-588, 1994.
DOI : 10.1109/83.334984

]. P. Van98 and . Vandergheynst, Directional Wavelets and Wavelets on the Sphere, 1998.

J. Vieron and C. Guillemot, Low rate fgs video compression based on motioncompensated spatio-temporal wavelet analysis, Proc. of the SPIE Intl Conference on Visual Communication and Image Processing VCIP'03, 2003.

V. N. Dang, A. R. Mansouri, and J. Konrad, Motion estimation for region-nased video coding, Proceedings of ICIP, 1995.

. J. Vpz98, K. Vass, X. Palaniappan, and . Zhuang, Automatic spatio-temporal video sequence segmentation, Proceedings of ICIP, IEEE International Conference on Image Processing, pp.958-962, 1998.

]. J. Wa94a, E. H. Wang, and . Adelson, Spatio-temporal segmentation of video data, Proceedings of SPIE on Image and Video Processing II, 2182, pp.120-131, 1994.

]. Y. Wa94b, E. H. Weiss, and . Adelson, Perceptually organized em : A framework for motion segmentation that combines information about form and motion, 1994.

]. S. Wen04 and . Wenger, A database of video sequences from the tml project. http ://www.stewe.org/vceg.org/sequences.htm Segmentation from motion : Combining gabor-and mallat-wavelets to overcome the aperture and correspondence problems, Wis99] L. Wiskott, pp.321751-1766, 1999.

Y. T. Wu, T. Kanade, J. Cohn, and C. C. Li, Optical flow estimation using wavelet motion model, Sixth International Conference on Computer Vision, pp.992-998, 1998.

G. [. Woods and . Lilienfeld, A resolution and frame-rate scalable subband/wavelet video coder, IEEE Transactions on Circuits and Systems for Video Technology, vol.11, issue.9, pp.1035-1044, 2001.
DOI : 10.1109/76.946520

J. [. Weber and . Malik, Robust computation of optical flow in a multi-scale differential framework, 1993 (4th) International Conference on Computer Vision, pp.67-81, 1995.
DOI : 10.1109/ICCV.1993.378240

A. Wang, Z. Xiong, P. A. Chou, and S. Mehrotra, Three-dimensional wavelet coding of video with global motion compensation, Proceedings DCC'99 Data Compression Conference (Cat. No. PR00096), p.404, 1999.
DOI : 10.1109/DCC.1999.755690

S. [. Xu, Y. Q. Li, Z. Zhang, and . Xiong, A wavelet video coder using three dimensional embedded subband coding with optimized truncation (3-d escot), Proceedings of IEEE Pacific-Rim Conference on Multimedia (PCM), 2000.

R. [. Aksoy and . Haralick, Content-based access of image and video libraries, Proceedings. IEEE Workshop on textural features for image database retrieval, pp.45-49, 1998.

]. C. Bha67 and . Bhattacharya, A simple method of resolution of resolution of a distribution into gaussian components, Biometrics, vol.23, pp.115-135, 1967.

P. Brault and A. Mohammad-djafari, Bayesian segmentation of video sequences using a Markov-Potts model, WSEAS Transactions on Mathematics, vol.3, issue.1, pp.276-282, 2004.

P. Brault and A. Mohammad-djafari, Bayesian Wavelet Domain Segmentation, AIP Conference Proceedings, pp.19-26, 2004.
DOI : 10.1063/1.1835193

URL : https://hal.archives-ouvertes.fr/hal-00533594

]. P. Bmd05a, A. Brault, and . Mohammad-djafari, Segmentation bayesienne dans le domaine ondelettes (poster), Colloque Alain BOUYSSY (sans actes) Février 2005. (poster présenté pour le Laboratoire des Signaux et Systèmes CNRS UMR8506/Supélec)

]. P. Bmd05b, A. Brault, and . Mohammad-djafari, Unsupervised bayesian wavelet domain segmentation using a potts-markov random field modeling, Journal of Electronic Imaging, 2005.

]. Boc04 and . Bock, Clustering methods -a review of classical and recent approaches, Proceedings of Modelling, Computation and Optimization in Information Systems and Management Sciences, 2004.

M. [. Bouman and . Shapiro, Multispectral image segmentation using a multiscale model, [Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing, pp.565-568, 1992.
DOI : 10.1109/ICASSP.1992.226150

M. [. Bouman and . 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

B. B. Coleman and H. C. Andrews, Image segmentation by clustering, Proceedings of IEEE, pp.773-785, 1979.
DOI : 10.1109/PROC.1979.11327

]. J. Can86 and . Canny, A computational approach to edge detection, IEEE Transactions on PAMI, vol.8, issue.6, pp.679-698, 1986.

R. [. Crouse and . Baraniuk, Contextual hidden Markov models for wavelet-domain signal processing, Conference Record of the Thirty-First Asilomar Conference on Signals, Systems and Computers (Cat. No.97CB36136), pp.95-100, 1997.
DOI : 10.1109/ACSSC.1997.680036

R. [. Choi and . Baraniuk, Image segmentation using wavelet-domain classification
DOI : 10.1117/12.351325

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.23.9809

]. H. Cb01a, C. A. Cheng, and . Bouman, Multiscale Bayesian segmentation using a trainable context model, IEEE Transactions on Image Processing, vol.10, issue.4, pp.51-525, 2001.

]. H. Cb01b, R. G. Choi, and . Baraniuk, Multiscale image segmentation using wavelet-domain hidden Markov models, IEEE Transactions on Image Processing, vol.10, issue.9, pp.1309-1321, 2001.

C. [. Conners and . Harlow, A Theoretical Comparison of Texture Algorithms, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.2, issue.3, pp.204-222, 1980.
DOI : 10.1109/TPAMI.1980.4767008

R. [. Crouse, R. G. Nowak, and . Baraniuk, Wavelet-based statistical signal processing using hidden Markov models, IEEE Transactions on Signal Processing, vol.46, issue.4, pp.886-902, 1998.
DOI : 10.1109/78.668544

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.320.2336

S. [. Cocquerez and . Philipp, Analyse d'Images : Filtrage et Segmentation, 1995.
URL : https://hal.archives-ouvertes.fr/hal-00706168

]. G. Dem02 and . Demoment, Probabilités : modélisation des incertitudes, inférence logique, et traitement des données expérimentalesPremì ere partie : bases de la théorie. Cours de l, Faculté des Sciences d'Orsay, Groupe desProbì emes Inverses, Laboratoire des Signaux et Systèmes, 2002.

. Ist-m2r-sseti, Master en information, systèmes et technologie de l'Université de Paris- Sud, Centre d'Orsay (formationàformationà la recherche en sciences des systèmes embarqués et traitement de l'information), Groupe desProbì emes Inverses, Laboratoire des Signaux et Systèmes, 2004.

]. R. Der87 and . 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.

O. Féron and A. Mohammad-djafari, A hidden Markov model for Bayesian data fusion of multivariate signals, Proceedings of Fifth International Triennal Calcutta Symposium on Probability and Statistics, 2003.

O. Féron and A. Mohammad-djafari, Image fusion and unsupervised joint segmentation using a HMM and MCMC algorithms, Journal of Electronic Imaging, vol.14, issue.2, 2005.

X. [. Fan, . Xia-[-fx02-]-g, X. G. Fan, . Xiagg84-]-s, D. Geman et al., A joint multicontext and multiscale approach to Bayesian image segmentation Wavelet-based texture analysis and synthesis using hidden Markov models Stochastic relaxation, Gibbs distributions and the Bayesian restoration of image, GG00] P. Gerard and A. Gagalowicz. Three-dimensional model-based tracking using texture learning and matching. Pattern Recognition Letters, pp.2680-2688229, 1984.

S. Geman, D. Geman, and C. Graffigne, Locating Texture and Object Boundaries, Pattern Recognition Theory and Application, 1987.
DOI : 10.1007/978-3-642-83069-3_14

]. R. Har84, . G. Haralickhaz00-]-g, and . Hazel, Digital step edges from zero-crossings of second directional derivative Multivariate Gaussian MRF for multispectral scene segmentation and anomaly detection, IEEE Trans. on PAMI IEEE Transactions on Geoscience end Remote Sensing, vol.6, issue.383, pp.58-681199, 1984.

F. Humblot, A. Mohammad-djafarihsd73, ]. R. Haralick, K. Shanumugam, I. T. Dinsteinjay95-]-e et al., special issue on super-resolution imaging : Analysis, algorithms, and applications Texture features for image classification Hafiane and B. Zavidovique. Automating GIS image retrieval based on MCM) Idier. Approche bayésienne pour les problemes inverses Ichir and A. Mohammad-Djafari. Bayesian based source separation for nonstationary positive sources Probability Theory : The Logic of Science, ICIAR Bayesian Inference and Maximum Entropy Methods MaxEnt Workshops. Maxent04. [Jai89] A.K. Jain. Fundamental of Digital Image ProcessingJB83] B Julesz and Bergen. Textons. Bell Systems Technical Journal, 1883. [JD88] A.K. Jain and R.C. Dubes. Algorithms for Clustering Data, pp.610-621, 1973.

S. Jehan, E. Debreuve, M. Barlaud, and G. Aubert, Segmentation spatio-temporelle d'objets en mouvement dans une séquence vidéo par contours actifs déformables, Proceedings of RFIA, 2000.

B. Jourlin, J. C. Pinoli, and R. Zeboudj, Contrast definition and contour detection for logarithmic images, Journal of Microscopy, vol.60, issue.1, pp.33-40, 1988.
DOI : 10.1111/j.1365-2818.1989.tb02904.x

[. Julesz, Visual Pattern Discrimination, IEEE Transactions on Information Theory, vol.8, issue.2, pp.84-92, 1883.
DOI : 10.1109/TIT.1962.1057698

S. [. Keller and . Chen, Texture description and segmentation through fractal geometry, Computer Vision, Graphics, and Image Processing, vol.45, issue.2, pp.150-166, 1989.
DOI : 10.1016/0734-189X(89)90130-8

L. [. Kunlin, A. Lacassagne, and . Merigot, A fast image segmentation scheme, Proceedings. 2004 International Conference on Information and Communication Technologies: From Theory to Applications, 2004., 2004.
DOI : 10.1109/ICTTA.2004.1307774

]. D. Mac00 and . Mackay, Information Theory, Inference and Learning Algorithms, 2000.

]. S. Mal01 and . Mallat, A Wavelet Tour of Signal Processing, 1997.

. [. Mohammad-djafari, Detection-Estimation ; Graduated Course

O. [. Mohammadpour, A. Féron, and . Mohammad-djafari, Bayesian segmentation of hyperspectral images, AIP Conference Proceedings, 2004.
DOI : 10.1063/1.1835254

URL : https://hal.archives-ouvertes.fr/hal-00447132

W. [. Mallat and . Hwang, Singularity detection and processing with wavelets, IEEE Transactions on Information Theory, vol.38, issue.2, pp.617-643, 1992.
DOI : 10.1109/18.119727

S. [. Mallat and . Zhong, Characterization of signals from multiscale edges, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.14, issue.7, 1992.

]. A. Pen84 and . Pentland, Fractal-based description of natural scenes, IEEE Transactions on PAMI, pp.661-674, 1984.

J. Pesquet, H. Krim, H. Leporini, and E. Hamman, Bayesian approach to best basis selection, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings, 1996.
DOI : 10.1109/ICASSP.1996.548005

T. [. Peet and . Sahota, Surface Curvature as a Measure of Image Texture, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.7, issue.6, pp.734-738, 1985.
DOI : 10.1109/TPAMI.1985.4767733

J. Portilla, V. Strela, W. Wainwright, and E. P. Simoncelli, Image denoising using scale mixtures of gaussians in the wavelet domain, IEEE Transactions on Image Processing, vol.12, issue.11, p.12, 2003.
DOI : 10.1109/TIP.2003.818640

L. Rao, Towards a texture naming system, Proceedings of the IEEE fourth Conference on Visualization, 1993.

H. [. Romberg, R. G. Choi, and . Baraniuk, Bayesian tree-structured image modeling using wavelet-domain hidden Markov models, IEEE Transactions on Image Processing, vol.10, issue.7, pp.1056-1068, 2001.
DOI : 10.1109/83.931100

]. C. Rob96 and . Robert, Méthodes de Monte Carlo par chaines de Markov, Economica, 1996.

R. [. Simchony, . Chellapa, and Z. Lichtenstein, The graduated non-convexity algorithm for image estimation using compound Gauss-Markov field models, Proc. ICASSP89, 1989.

G. [. Song and . Fan, A study of supervised, semi-supervised and unsupervised multiscale Bayesian image segmentation, MWSCAS02, 45th Midwest Symposium on Circuits and Systems, pp.371-374, 2002.

]. X. Sf03a, G. Song, and . Fan, Unsupervised Bayesian image segmentation using wavelet-domain hidden Markov models, Proc. of ICIP, International Conference on Image Processin, pp.423-426, 2003.

]. X. Sf03b, G. Song, and . Fan, Unsupervised image segmentation using wavelet-domain hidden Markov models, Proceedings of SPIE Wavelets X in applications in signal and image processing, 2003.

G. [. Song and . Fan, Unsupervised image segmentation by exploiting likelihood disparity of texture behavior, pp.1-30, 2004.

]. J. Sha93 and . Shapiro, Embedded image coding using zerotrees of wavelet coefficients, IEEETSP, issue.12, pp.413445-3462, 1993.

V. [. Sonka, R. Hlavac, and . Boyle, Image Processing, Analysis and Machine Vision, 1999.
DOI : 10.1007/978-1-4899-3216-7

. Sip and . Sipi, Images and videos database

A. [. Snoussi and . Mohammad-djafari, Fast joint separation and segmentation of mixed images, Journal of Electronic Imaging, vol.13, issue.2, pp.349-361, 2002.
DOI : 10.1117/1.1666873

]. R. Vos86 and . Voss, Characterization and measurement of random fractals, Physica Scripta, vol.13, p.27, 1986.

L. [. Walter and . Pronzato, Identification de Modèles Paramétriques, ` a partir de données expérimentales. Modélisation Analyse Simulation Commande, 1994.

]. F. Wu82 and . Wu, The Potts model. Review of Modern Physics, pp.235-268, 1982.

R. [. Zerubia and . Chellapa, Mean field annealing using compound Gauss-Markov random fields for edge detection and image estimation, IEEE Transactions on Neural Networks, vol.4, issue.4, pp.703-709, 1993.
DOI : 10.1109/72.238324

P. Brault and A. Mohammad-djafari, Unsupervised bayesian wavelet domain segmentation using a potts-markov random field modeling, Journal of Electronic Imaging, 2005.
URL : https://hal.archives-ouvertes.fr/hal-00533594

P. Brault and A. Mohammad-djafari, Segmentation bayesienne dans le domaine ondelettes (poster) In Colloque Alain BOUYSSY (sans actes), Février 2005. (poster présenté pour le Laboratoire des Signaux et Systèmes CNRS UMR8506/Supélec)

P. Brault and A. Mohammad-djafari, Bayesian Wavelet Domain Segmentation, AIP Conference Proceedings, pp.19-26, 2004.
DOI : 10.1063/1.1835193

URL : https://hal.archives-ouvertes.fr/hal-00533594

P. Brault and A. Mohammad-djafari, Bayesian segmentation of video sequences using a Markov-Potts model, WSEAS Transactions on Mathematics, vol.3, issue.1, pp.276-282, 2004.

P. Brault, On the performances and improvements of motion-tuned wavelets for motion estimation, WSEAS Transactions on Electronics, vol.1, issue.1, pp.174-180, 2004.

P. Brault, A new scheme for object-oriented video compression and scene analysis based on motion tuned spatio-temporal wavelet family trajectory identification, Proceedings of the 3rd IEEE International Symposium on Signal Processing and Information Technology (IEEE Cat. No.03EX795), 2003.
DOI : 10.1109/ISSPIT.2003.1341107

P. Brault and M. Vasiliu, Motion-compensated spatio-temporal filtering with wavelets, WSEAS Transactions on Computers, vol.2, issue.4, pp.1131-1140, 2003.

P. Brault, Motion estimation and video compression with spatio-temporal motion-tuned wavelets, WSEAS Transactions on Mathematics, vol.2, issue.1 2, pp.67-78, 2003.

P. Brault, J. L. Starck, and P. Beauvillain, Characterization of nanostructures stm images with the wavelet and ridgelet transforms, Proceedings of the IAPR-ICISP, International Conference on Image and Signal Processing, pp.232-241, 2003.

P. Brault and H. Mounier, <title>Automated transformation-invariant shape recognition through wavelet multiresolution</title>, Wavelets: Applications in Signal and Image Processing IX
DOI : 10.1117/12.449735

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.5.8893

A. Michael and . Unser, Akram Aldroubi, pp.434-443, 2001.

P. Brault and H. Mounier, Wavelet multi-resolution transform applied to shape recognition based on a curvature criterion, Proceedings of the IAPR International Conference on Image and Signal Processing, pp.250-258, 2001.

P. Brault, H. Mounier, N. Petit, and P. Rouchon, Flatness based tracking control of a manoeuvrable vehicle : the ? ? car, Proceedings of the MTNS, International Conference on Mathematical Theory of Networks and Systems, pp.1-7, 2000.

C. Goutelard and P. Brault, Fractal approach of the ionospheric channel scattering function, Proceedings of the COST 257 Congress, El Arenosillo, 1999.

P. Brault, Engineer thesis : Fractal analysis of the random propagation channels in the ionosphere, 1998.

P. Brault, Digital phase-locked loops. engineer cycle probing oral. dir. M. Bellanger, 1996.