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Estimation of a motion field on satellite images from a simplified ocean circulation model

Abstract : This paper aims at estimating the apparent velocity from sequences of satellite images. This study is an illustration of a more general methodology for generating, from satellite images, pseudo-observations of physical variables, that are assimilated within a geophysical forecast model in view of improving the quality of its results. In the case of the presented study, the used satellite images are sequences of Sea Surface Temperature (SST), from which pseudo-observations of sea surface velocities are generated, and assimilated within an ocean circulation model. The originality of the approach lies in the definition of an Image Model, that predicts the evolution of image information -here, SST- as a function of the pseudo-observations -here, surface velocity-. Satellite data are then assimilated within the Image Model, yielding an estimation of the pseudo-observations. In the case of this paper, this methods allows the estimation of sea surface velocities, even when large parts of the satellite images are corrupted by clouds. The Image Model plays the role of an intermediate model, between satellite data and the forecast model, and allows the assimilation of image information which is not directly linked to the state variables of the forecast model.
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Contributor : Nathalie Gaudechoux Connect in order to contact the contributor
Submitted on : Friday, February 26, 2021 - 5:00:47 PM
Last modification on : Friday, January 21, 2022 - 3:17:43 AM
Long-term archiving on: : Thursday, May 27, 2021 - 6:56:44 PM


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Isabelle Herlin, Etienne Huot, Jean-Paul Berroir, François-Xavier Le Dimet, Gennady K. Korotaev. Estimation of a motion field on satellite images from a simplified ocean circulation model. ICIP 2006 International Conference on Image Processing, IEEE, Oct 2006, Atlanta, United States. pp.1077-1080, ⟨10.1109/ICIP.2006.312742⟩. ⟨inria-00604618⟩



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