Analysis of SST images by Weighted Ensemble Transform Kalman Filter, Geoscience and Remote Sensing Symposium (IGARSS), pp.4172-4175, 2011. ,
Assimilation de température de surface par filtre de Kalman de transformation d'ensemble pondéré, GRETSI, september 2011. URL http ,
Multiscale Weighted Ensemble Kalman Filter for Fluid Flow Estimation, Lecture Notes in Computer Science, vol.6667, pp.749-760 ,
DOI : 10.1007/978-3-642-24785-9_63
Fluid Flow Estimation with Multiscale Ensemble Filters Based on Motion Measurements Under Location Uncertainty Numerical Mathematics: Theory, Methods and Applications Weighted Eensemble Transform Kalman Filter for Image Assimilation, Tellus A, vol.6, issue.65, pp.21-46, 2013. ,
Les deuxpremì eres ont une décorrélation spatiale isotrope, contrairementàcontrairementà ladernì ere qui a une décorrélation anisotrope orientée de 3/4? radians, p.58 ,
isotrope) pour le bruit d'Evensen, ici r x = 13, sur une image de 256 × 256 pixels, avec les paramètres usuels utilisés lors de l'assimilation, p.61 ,
a droite) de différentes méthodes : Corpetti and Mémin, HéasPapadakis and Mémin, p.91, 2007. ,
Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables, 1964. ,
An Ensemble Adjustment Kalman Filter for Data As- similation ,
Méthodes de filtrage pour du suivi dans des séquences d'images -Application au suivi de points caractéristiques, 2004. ,
Partial Linear Gaussian Models for Tracking in Image Sequences Using Sequential Monte Carlo Methods, pp.75-102, 2007. ,
URL : https://hal.archives-ouvertes.fr/hal-00171409
A Database and Evaluation Methodology for Optical Flow, International Journal of Computer Vision, vol.27, issue.3, pp.1-31, 2011. ,
DOI : 10.1007/s11263-010-0390-2
Performance of optical flow techniques, International Journal of Computer Vision, vol.54, issue.1, pp.43-77, 1994. ,
DOI : 10.1007/BF01420984
Assimilation de température de surface par filtre de Kalman de transformation d'ensemble pondéré, GRETSI, september 2011. URL http ,
Fluid Flow Estimation with Multiscale Ensemble Filters Based on Motion Measurements Under Location Uncertainty, Numerical Mathematics : Theory, Methods and Applications, vol.6, pp.21-46, 2013. ,
URL : https://hal.archives-ouvertes.fr/hal-00736457
Weighted Eensemble Transform Kalman Filter for Image Assimilation, Tellus A, vol.65, 2013. ,
Adaptive Sampling with the Ensemble Transform Kalman Filter. Part I: Theoretical Aspects, Monthly Weather Review, vol.129, issue.3, pp.420-4361520, 2001. ,
DOI : 10.1175/1520-0493(2001)129<0420:ASWTET>2.0.CO;2
Optimisation d'un filtre particulaire en contexte Track-Before-Detect, GRETSI, 2011. ,
URL : https://hal.archives-ouvertes.fr/hal-00911889
Introduction aux principes et méthodes de l'assimilation de donnéees en géophysique, 2004. ,
Data assimilation in glaciology, Advanced Data Assimilation for Geosciences ,
DOI : 10.1093/acprof:oso/9780198723844.003.0025
URL : https://hal.archives-ouvertes.fr/hal-00715832
Stochastic uncertainty models for the luminance consistency assumption, Image Processing IEEE Transactions on, issue.99 ,
Pressure image assimilation for atmospheric motion estimation. Tellus A, pp.160-178, 2009. ,
URL : https://hal.archives-ouvertes.fr/inria-00273838
Particle Filters ??? A Theoretical Perspective, Sequential Monte Carlo Methods in Practice, chapter, 2001. ,
DOI : 10.1007/978-1-4757-3437-9_2
Branching and interacting particle systems approximations of Feynman-Kac formulae with applications to non-linear filtering, Lecture Notes in Mathematics, vol.1729, pp.1-145, 2000. ,
Ondelettes et Estimation de Mouvements de Fluide ,
The Kalman Filter for Complex Fibonacci Systems, ISRN Signal Processing, 2012. ,
DOI : 10.1016/j.sigpro.2010.11.007
On sequential Monte Carlo sampling methods for Bayesian filtering, Statistics and Computing, vol.10, issue.3, pp.197-208, 2000. ,
DOI : 10.1023/A:1008935410038
Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics, Journal of Geophysical Research, vol.109, issue.Part 4, pp.9910143-10162, 1994. ,
DOI : 10.1029/94JC00572
The Ensemble Kalman Filter: theoretical formulation and practical implementation, Ocean Dynamics, vol.53, issue.4, pp.343-367, 2003. ,
DOI : 10.1007/s10236-003-0036-9
Sampling strategies and square root analysis schemes for the EnKF, Ocean Dynamics, vol.54, issue.6, pp.539-560, 2004. ,
DOI : 10.1007/s10236-004-0099-2
Recovering Motion Fields: An Evaluation of Eight Optical Flow Algorithms, Procedings of the British Machine Vision Conference 1998, pp.195-204, 1998. ,
DOI : 10.5244/C.12.20
Novel approach to nonlinear/non- Gaussian Bayesian state estimation. Radar and Signal Processing, IEE Proceedings F, vol.140, issue.2, pp.107-113, 1993. ,
Multiscale Weighted Ensemble Kalman Filter for Fluid Flow Estimation, Scale Space and Variational Methods in Computer Vision, pp.749-760 ,
DOI : 10.1007/978-3-642-24785-9_63
URL : https://hal.archives-ouvertes.fr/hal-00694975
Analysis of SST images by Weighted Ensemble Transform Kalman Filter, Geoscience and Remote Sensing Symposium (IGARSS), pp.4172-4175, 2011. ,
URL : https://hal.archives-ouvertes.fr/hal-00694594
Scrum manuel, 1997. ,
History matching of petroleum reservoir models by the Ensemble Kalman Filter and parameterization methods, Computers & Geosciences, vol.55 ,
DOI : 10.1016/j.cageo.2012.06.006
URL : https://hal.archives-ouvertes.fr/hal-00818367
Variational fluid flow measurements from image sequences: synopsis and perspectives, Experiments in Fluids, vol.28, issue.4, pp.369-393, 2010. ,
DOI : 10.1007/s00348-009-0778-3
URL : https://hal.archives-ouvertes.fr/hal-00456162
Ensemble Kalman filtering, Quarterly Journal of the Royal Meteorological Society, vol.109, issue.613, pp.3269-3289, 2005. ,
DOI : 10.1256/qj.05.135
Bayesian selection of scaling laws for motion modeling in images, 2009 IEEE 12th International Conference on Computer Vision, pp.971-978, 2009. ,
DOI : 10.1109/ICCV.2009.5459353
Unified Notation for Data Assimilation : Operational, Sequential and Variational, Journal of the Meteorological Society of Japan, vol.75, issue.1B, pp.181-189, 1997. ,
SMCTC : Sequential Monte Carlo in C++, Journal of Statistical Software, vol.30, issue.4, pp.1-41, 2009. ,
Unscented Filtering and Nonlinear Estimation, Proceedings of the IEEE, vol.92, issue.3, pp.401-422, 2004. ,
DOI : 10.1109/JPROC.2003.823141
A New Extension of the Kalman Filter to Nonlinear Systems, Int. Symp. Aerospace/Defense Sensing, Simul. and Controls, pp.182-193, 1997. ,
A New Approach to Linear Filtering and Prediction Problems, Journal of Basic Engineering, vol.82, issue.1, pp.35-45, 1960. ,
DOI : 10.1115/1.3662552
Small-Scale Structure of a Scalar Field Convected by Turbulence, Physics of Fluids, vol.11, issue.5, pp.945-953, 1968. ,
DOI : 10.1063/1.1692063
A Third-Order Semidiscrete Central Scheme for Conservation Laws and Convection-Diffusion Equations, SIAM Journal on Scientific Computing, vol.22, issue.4, pp.1461-1488, 2000. ,
DOI : 10.1137/S1064827599360236
Variational algorithms for analysis and assimilation of meteorological observations : theoretical aspects. Tellus A, 1986. ,
Large Sample Asymptotics for the Ensemble Kalman Filter ,
Large sample asymptotics for the ensemble Kalman filter The Oxford Handbook of Nonlinear Filtering, pp.598-631, 2011. ,
The impact of ensemble filter definition on the assimilation of temperature profiles in the tropical Pacific, Quarterly Journal of the Royal Meteorological Society, vol.130, issue.613, pp.3291-3300, 2005. ,
DOI : 10.1256/qj.05.90
Elements of Large-Sample Theory Springer Texts in Statistics, 1999. ,
An iterative image registration technique with an application to stereo vision, Proceedings of Imaging Understanding Workshop, pp.121-130, 1981. ,
Attack detection in Water Supply Systems using Kalman filter estimator, 2012 35th IEEE Sarnoff Symposium, pp.1-6 ,
DOI : 10.1109/SARNOF.2012.6222737
Estimation du flot optique : contribution et panorama de différentes approches, 2003. ,
Improving Regularised Particle Filters, Sequential Monte Carlo Methods in Practice, pp.247-271978, 2001. ,
DOI : 10.1007/978-1-4757-3437-9_12
An Efficient Implementation of the Ensemble Kalman Filter Based on an Iterative Sherman-Morrison Formula. CoRR, abs/1302, 2013. ,
Assimilation de données images : application au suivi de courbes et de champs de vecteurs, 2007. ,
Variational assimilation of fluid motion from image sequence, In SIAM J. Imag. Sci, vol.1, pp.343-363, 2007. ,
Data assimilation with the weighted ensemble Kalman filter. Tellus A, pp.673-697, 2010. ,
URL : https://hal.archives-ouvertes.fr/hal-00490840
The Use of an Ensemble Approach to Study the Background Error Covariances in a Global NWP Model, Mon. Wea. Rev, vol.134, issue.9, pp.2466-2489, 2006. ,
Localization in the ensemble Kalman Filter, 2008. ,
Stochastic Methods for Sequential Data Assimilation in Strongly Nonlinear Systems ,
URL http://dx.doi.org/10, 129¡1194 :SMFSDA¿2.0.CO, pp.1194-12071520, 1175. ,
A singular evolutive extended Kalman filter for data assimilation in oceanography, Journal of Marine Systems, vol.16, issue.3-4, pp.323-340, 1998. ,
DOI : 10.1016/S0924-7963(97)00109-7
Auxiliary Variable Based Particle Filters, Sequential Monte Carlo Methods in Practice, pp.273-293978, 2001. ,
Data assimilation for short range atmospheric dispersion of radionuclides: a case study of second-order sensitivity, Journal of Environmental Radioactivity, vol.84, issue.3, pp.393-408, 2005. ,
DOI : 10.1016/j.jenvrad.2005.04.011
Implications of the Form of the Ensemble Transformation in the Ensemble Square Root Filters, Monthly Weather Review, vol.136, issue.3, pp.1042-1053, 2001. ,
DOI : 10.1175/2007MWR2021.1
The regional oceanic modeling system (ROMS) : a split-explicit, free-surface, topography-following-coordinate oceanic model. Ocean Modelling, pp.347-404, 2005. ,
State Estimation and the Meaning of Life, pp.493-499, 2006. ,
Filtrage particulaire sur les variétés riemanniennes, Gretsi, 2011. ,
Assimilation d'images pour les fluides géophysiques ,
Amélioration des prévisions d'ensemble des débits sur la France de SAFRAN-ISBA-MODCOU, 2009. ,
Ensemble Square Root Filters, Monthly Weather Review, vol.131, issue.7, pp.1485-1490, 2003. ,
Assimilating transient groundwater flow data via a localized ensemble Kalman filter to calibrate a heterogeneous conductivity field, Stochastic Environmental Research and Risk Assessment, vol.22, issue.2, pp.467-478, 2012. ,
DOI : 10.1007/s00477-011-0534-0
Particle Filtering in Geophysical Systems, Monthly Weather Review, vol.137, issue.12, pp.4089-4114, 2001. ,
DOI : 10.1175/2009MWR2835.1
Assimilation of OMI NO2 retrievals into a regional chemistry-transport model for improving air quality forecasts over Europe, Atmospheric Environment, vol.45, issue.2, pp.485-492, 2011. ,
DOI : 10.1016/j.atmosenv.2010.09.028
URL : https://hal.archives-ouvertes.fr/inria-00582482
Note on a Method for Calculating Corrected Sums of Squares and Products, Technometrics, vol.1, issue.1, pp.419-420, 1962. ,
DOI : 10.1080/00401706.1962.10490022
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
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.529.4121