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Sparse analysis for mesoscale convective systems tracking

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Date
2020
Publisher city
Paris
Dewey
Analyse
Sujet
Sparse image analysis; Mesoscale Convective System tracking; Shape tracking; Remote sensing image processing; Gridless sparse analysis
Journal issue
Signal Processing: Image Communication
Volume
85
Publication date
2020
Article pages
115854
DOI
http://dx.doi.org/10.1016/j.image.2020.115854
URI
https://basepub.dauphine.fr/handle/123456789/18672
Collections
  • CEREMADE : Publications
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Author
Courbot, Jean-Baptiste
541698 Laboratoire de Météorologie Dynamique (UMR 8539) [LMD]
529779 Institut de Recherche en Informatique Mathématiques Automatique Signal [IRIMAS]
Duval, Vincent
60 CEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
Legras, Bernard
541698 Laboratoire de Météorologie Dynamique (UMR 8539) [LMD]
463928 Université Paris 1, Panthéon-Sorbonne [UP1]
Type
Article accepté pour publication ou publié
Abstract (EN)
In this paper, we study the tracking of deformable shapes in sequences of images. Our target application is the tracking of clouds in satellite images. 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 a method to handle the tracking with its specificities: apparition or disappearance of objects, merging, and splitting. Numerically, this method corroborates the magnitude of the results provided by recent state-of-the-art alternatives. Unlike its counterparts, the choice or regularization and correlation parameters allows additional flexibility regarding the interpretation of clouds’ life cycles. Finally, it also provides additional information on the cloud temperature during its life cycle, which seem in accordance with the underlying physical processes

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