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| Fablet, Ronan; Viet, P.; Lguensat, R.; Chapron, Bertrand. |
| We address in this paper the reconstruction of irregurlarlysampled image time series with an emphasis on geophysical remote sensing data. We develop a data-driven approach, referred to as an analog assimilation and stated as an ensemble Kalman method. Contrary to model-driven assimilation models, we do not exploit a physically-derived dynamic prior but we build a data-driven dynamic prior from a representative dataset of the considered image dynamics. Our contribution is here to extend analog assimilation to images, which involve high-dimensional state space.We combine patch-based representations to a multiscale PCA-constrained decomposition. Numerical experiments for the interpolation of missing data in satellite-derived ocean remote sensing images... |
| Tipo: Text |
Palavras-chave: Data assimilation; Irregular sampling; Image time series; Data-driven methods; Kalman methods. |
| Ano: 2017 |
URL: https://archimer.ifremer.fr/doc/00403/51440/52009.pdf |
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