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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.
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Contributor : Jean-Baptiste Courbot <>
Submitted on : Thursday, February 7, 2019 - 10:59:57 AM
Last modification on : Thursday, April 2, 2020 - 1:28:58 PM
Document(s) archivé(s) le : Wednesday, May 8, 2019 - 1:56:01 PM


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  • HAL Id : hal-02010436, version 1


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



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