Multiscale Weighted Ensemble Kalman Filter for Fluid Flow Estimation
Résumé
This paper proposes a novel multi-scale uid ow data as- similation approach, which integrates and complements the advantages of a Bayesian sequential assimilation technique, the Weighted Ensem- ble Kalman lter (WEnKF) [12], and an improved multiscale stochastic formulation of the Lucas-Kanade (LK) estimator. The proposed scheme enables to enforce a physically plausible dynamical consistency of the estimated motion elds along the image sequence. 1
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