Segmentation, tracking and characterization of solar features from EIT solar corona images

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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. © 2009 Springer Berlin Heidelberg.

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Barra, V., Delouille, V., & Hochedez, J. F. (2009). Segmentation, tracking and characterization of solar features from EIT solar corona images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5575 LNCS, pp. 199–208). https://doi.org/10.1007/978-3-642-02230-2_21

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