Segmentation, Tracking and Characterization of Solar Features from EIT Solar Corona Images

Abstract : With the multiplication of sensors and instruments, size, amount and quality of solar image data are constantly increasing, and analyzing this data requires defining and implementing accurate and reliable algorithms. In the context of solar features analysis, it is particularly important to accurately delineate their edges and track their motion, to estimate quantitative indices and analyse their evolution through time. Herein, we introduce an image processing pipeline that segment, track and quantify solar features from a set of multispectral solar corona images , taken with eit EIT instrument. We demonstrate the method on the automatic tracking of Active Regions from EIT images, and on the analysis of the spatial distribution of coronal bright points. The method is generic enough to allow the study of any solar feature, provided it can be segmented from EIT images or other sources.
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Proceedings of SCIA 2009, Lecture Notes in Computer Sciences, Jun 2009, Oslo, Norway. 〈10.1007/978-3-540-30134-9_60〉
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https://hal-clermont-univ.archives-ouvertes.fr/hal-01622910
Contributeur : Vincent Barra <>
Soumis le : mardi 24 octobre 2017 - 18:00:10
Dernière modification le : lundi 5 février 2018 - 09:24:56

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Vincent Barra, Véronique Delouille, Jean-François Hochedez. Segmentation, Tracking and Characterization of Solar Features from EIT Solar Corona Images. Proceedings of SCIA 2009, Lecture Notes in Computer Sciences, Jun 2009, Oslo, Norway. 〈10.1007/978-3-540-30134-9_60〉. 〈hal-01622910〉

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