Sparse analysis for mesoscale convective systems tracking

Abstract : In this paper, we study the tracking of de-formable shapes in sequences of images. Our target application is the tracking of clouds in satellite image. We propose to use a recent state-of-the-art method for off-the-grid sparse analysis to describe clouds in image as mixtures of 2D atoms. Then, we introduce an algorithm to handle the tracking with its specificities: apparition or disappearance of objects, merging, and splitting. This method provides similar numerical outputs as the recent state-of-the-art alternatives, while being more flexible, and providing additional information on, e.g., cloud surface brightness.
Type de document :
Pré-publication, Document de travail
2019
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https://hal.archives-ouvertes.fr/hal-02010436
Contributeur : Jean-Baptiste Courbot <>
Soumis le : jeudi 7 février 2019 - 10:59:57
Dernière modification le : mardi 12 février 2019 - 01:09:53

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  • HAL Id : hal-02010436, version 1

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Jean-Baptiste Courbot, Vincent Duval, Bernard Legras. Sparse analysis for mesoscale convective systems tracking. 2019. 〈hal-02010436〉

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