A. Bennet, Inverse Methods in Physical Oceanography, 1992.
DOI : 10.1017/CBO9780511600807

F. Bouttier and P. Courtier, Data assimilation concepts and methods. ECMWF Meteorological Training Course Lecture Series, 1999.

T. Corpetti, D. Heitz, G. Arroyo, E. Mémin, and A. Santa-cruz, Fluid experimental flow estimation based on an optical-flow scheme, Experiments in Fluids, vol.10, issue.5, pp.80-97, 2006.
DOI : 10.1007/s00348-005-0048-y

URL : https://hal.archives-ouvertes.fr/halshs-00008138

T. Corpetti, E. Mémin, and P. Pérez, Dense estimation of fluid flows, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.24, issue.3, pp.365-380, 2002.
DOI : 10.1109/34.990137

URL : https://hal.archives-ouvertes.fr/hal-00329724

P. Courtier and O. Talagrand, Variational assimilation of meteorological observations with the direct and adjoint shallow-water equations, Tellus A: Dynamic Meteorology and Oceanography, vol.45, issue.5, pp.531-549, 1990.
DOI : 10.3402/tellusa.v42i5.11896

A. Cuzol, P. Hellier, and E. Memin, A low dimensional fluid motion estimator . Accepted for publication in Int, J. of Comput. Vis, 2007.
URL : https://hal.archives-ouvertes.fr/inserm-00140892

J. D. Adamo, N. Papadakis, E. Mémin, and A. G. , Variational assimilation of pod low-order dynamical systems, Journal of Turbulence, vol.8, issue.9, pp.1-22, 2007.
URL : https://hal.archives-ouvertes.fr/hal-00596160

P. and D. Mey, Data assimilation at th oceanic mesoscale: a review, J. Meteor. Soc. Jap, vol.75, pp.415-427, 1997.

A. De-saint-venant, Théorie du mouvement non-permanent des eaux, avec application aux crues desrivì eres etàet`età l'introduction des marées dans leur lit, C. R. Acad. Sc. Paris, vol.73, pp.147-154, 1871.

D. Geman and G. Reynolds, Constrained restoration and the recovery of discontinuities, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.14, issue.3, pp.367-383, 1992.
DOI : 10.1109/34.120331

P. Ghil and . Malanotte-rizzoli, Data Assimilation in Meteorology and Oceanography, Adv. Geophys, vol.23, pp.141-266, 1991.
DOI : 10.1016/S0065-2687(08)60442-2

P. Héas, E. Mémin, N. Papadakis, and A. Szantai, Layered Estimation of Atmospheric Mesoscale Dynamics From Satellite Imagery, IEEE Transactions on Geoscience and Remote Sensing, vol.45, issue.12, 2007.
DOI : 10.1109/TGRS.2007.906156

P. Holland and R. Welsch, Robust regression using iteratively reweighted least-squares, Communications in Statistics - Theory and Methods, vol.3, issue.9, pp.813-827, 1977.
DOI : 10.1214/aos/1176342503

J. Holton, An introduction to dynamic meteorology. Academic press, 1992.

M. Honnorat, F. Dimet, and J. Monnier, On a river hydraulics model and Lagrangian data assimilation, International Conference on Adaptive Modeling and Simulation, ADMOS'05, 2005.
URL : https://hal.archives-ouvertes.fr/inria-00259911

B. Horn and B. Schunck, Determining optical flow, Artificial Intelligence, vol.17, issue.1-3, pp.185-203, 1981.
DOI : 10.1016/0004-3702(81)90024-2

A. Kurganov and E. Tadmor, New High-Resolution Central Schemes for Nonlinear Conservation Laws and Convection???Diffusion Equations, Journal of Computational Physics, vol.160, issue.1, pp.241-282, 2000.
DOI : 10.1006/jcph.2000.6459

F. Dimet and J. Blum, Assimilation de données pour les fluides géophysiques. MATAPLI, Bulletin de la SMAI, pp.35-55, 2002.

F. Dimet and O. Talagrand, Variational algorithms for analysis and assimilation of meteorological observations: theoretical aspects, Tellus A, vol.109, issue.2, pp.97-110, 1986.
DOI : 10.1111/j.1600-0870.1986.tb00459.x

J. Leese, C. Novack, and B. Clark, An Automated Technique for Obtaining Cloud Motion from Geosynchronous Satellite Data Using Cross Correlation, Journal of Applied Meteorology, vol.10, issue.1, pp.118-132, 1971.
DOI : 10.1175/1520-0450(1971)010<0118:AATFOC>2.0.CO;2

J. Lions, Optimal control of systems governed by PDEs, 1971.

B. Lucas and T. Kanade, An iterative image registration technique with an application to stereovision, Int. Joint Conf. on Artificial Intel. (IJCAI), pp.674-679, 1981.

N. N. Mansour, J. H. Ferziger, and W. C. Reynolds, Large-eddy simulation of a turbulent mixing layer, 1978.

E. Mémin and P. Pérez, 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.
DOI : 10.1109/83.668027

B. Oksendal, Stochastic differential equations, 1998.
URL : https://hal.archives-ouvertes.fr/inria-00560229

N. Papadakis, T. Corpetti, and E. Mémin, Dynamically consistent optical flow estimation, 2007 IEEE 11th International Conference on Computer Vision, 2007.
DOI : 10.1109/ICCV.2007.4408889

URL : https://hal.archives-ouvertes.fr/hal-00596200

N. Papadakis and M. , A variational method for joint tracking of curve and motion, 2007.
URL : https://hal.archives-ouvertes.fr/inria-00171087

N. Papadakis and E. Mémin, Variational optimal control technique for the tracking of deformable objects, 2007 IEEE 11th International Conference on Computer Vision, 2007.
DOI : 10.1109/ICCV.2007.4408944

URL : https://hal.archives-ouvertes.fr/hal-00596203

P. Ruhnau and C. Schnörr, Optical Stokes flow estimation: an imaging-based control approach, Experiments in Fluids, vol.15, issue.3, pp.61-78, 2007.
DOI : 10.1007/s00348-006-0220-z

P. Sagaut, Large-eddy simulation for incompressible flow -An introduction, third edition, 2005.

J. Schmetz, K. Holmlund, J. Hoffman, B. Strauss, B. Mason et al., Operational Cloud-Motion Winds from Meteosat Infrared Images, Journal of Applied Meteorology, vol.32, issue.7, pp.321206-1225, 1993.
DOI : 10.1175/1520-0450(1993)032<1206:OCMWFM>2.0.CO;2

J. Smagorinsky, GENERAL CIRCULATION EXPERIMENTS WITH THE PRIMITIVE EQUATIONS, Monthly Weather Review, vol.91, issue.3, pp.99-164, 1963.
DOI : 10.1175/1520-0493(1963)091<0099:GCEWTP>2.3.CO;2

O. Talagrand, Assimilation of observations, an introduction, J. Meteor. Soc. Jap, vol.75, pp.191-209, 1997.

O. Talagrand and P. Courtier, Variational Assimilation of Meteorological Observations With the Adjoint Vorticity Equation. I: Theory, Quarterly Journal of the Royal Meteorological Society, vol.8, issue.10, pp.1311-1328, 1987.
DOI : 10.1002/qj.49711347812

G. Taylor, The Transport of Vorticity and Heat through Fluids in Turbulent Motion, Proc London Math Soc. Ser A, pp.151-421, 1932.
DOI : 10.1098/rspa.1932.0061

J. Templeton, M. Wang, and P. Moin, An efficient wall model for largeeddy simulation based on optimal control theory, Phys. of Fluids, vol.18, issue.2, 2006.

Z. Xu and C. Shu, Anti-diffusive finite difference weno methods for shallow water with transport of pollutant, Journal of Computational Mathematics, vol.24, pp.239-251, 2006.

I. Yu, G. Gejadze, I. Copeland, and . Navon, Open boundary control problem for navier-stokes equations including a free surface: Data assimilation, Comput. Math. Appl, vol.52, pp.8-91269, 2006.

J. Yuan, C. Schnoerr, and E. Mémin, Discrete Orthogonal Decomposition and Variational Fluid Flow Estimation, Journal of Mathematical Imaging and Vision, vol.34, issue.2, pp.67-80, 2007.
DOI : 10.1007/s10851-007-0014-9

L. Zhou, C. Kambhamettu, and D. Goldgof, Fluid structure and motion analysis from multi-spectrum 2D cloud image sequences, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662)
DOI : 10.1109/CVPR.2000.854949

. Comp, Vision Pattern Rec, pp.744-751, 2000.

T. Estimation and P. Of, 13 4.2.1 State variables 13 4.2.2 Observation operator, p.16

T. Estimation and .. Of-filtered-wind-fields, 18 5.2.1 Cost function and state variables, p.20

S. Synthetic-image, 20 6.1.1 Perfect scheme, p.23