Article Dans Une Revue Signal Processing: Image Communication Année : 2020

Sparse analysis for mesoscale convective systems tracking

Jean-Baptiste Courbot
Vincent Duval

Résumé

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.

Fichier principal
Vignette du fichier
SAST_soumis-HAL.pdf (5.43 Mo) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)
Licence

Dates et versions

hal-03008714 , version 1 (07-02-2019)
hal-03008714 , version 2 (16-09-2020)
hal-03008714 , version 3 (16-11-2020)

Licence

Identifiants

Citer

Jean-Baptiste Courbot, Vincent Duval, Bernard Legras. Sparse analysis for mesoscale convective systems tracking. Signal Processing: Image Communication, 2020, 85, pp.115854. ⟨10.1016/j.image.2020.115854⟩. ⟨hal-03008714v3⟩
694 Consultations
484 Téléchargements

Altmetric

Partager

  • More