Tracking of coronal white-light events by texture

The extraction of the kinematic properties of coronal mass ejections (CMEs) from white-light coronagraph images involves a significant degree of user interaction: defining the edge of the event, separating the core from the front or from nearby unrelated structures, etc. To contribute towards a less...

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Detalles Bibliográficos
Publicado: 2010
Materias:
Automatic tracking
CME
Coronagraph
Acceso en línea:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_00380938_v262_n2_p481_Goussies
http://hdl.handle.net/20.500.12110/paper_00380938_v262_n2_p481_Goussies
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
id paper:paper_00380938_v262_n2_p481_Goussies
record_format dspace
spelling paper:paper_00380938_v262_n2_p481_Goussies2023-06-08T15:02:44Z Tracking of coronal white-light events by texture Automatic tracking CME Coronagraph The extraction of the kinematic properties of coronal mass ejections (CMEs) from white-light coronagraph images involves a significant degree of user interaction: defining the edge of the event, separating the core from the front or from nearby unrelated structures, etc. To contribute towards a less subjective and more quantitative definition, and therefore better kinematic characterization of such events, we have developed a novel image-processing technique based on the concept of "texture of the event". The texture is defined by the so-called gray-level co-occurrence matrix, and the technique consists of a supervised segmentation algorithm to isolate a particular region of interest based upon its similarity with a pre-specified model. Once the event is visually defined early in its evolution, it is possible to automatically track the event by applying the segmentation algorithm to the corresponding time series of coronagraph images. In this paper we describe the technique, present some examples, and show how the coronal background, the core of the event, and even the associated shock (if one exists) can be identified for different kind of CMEs detected by the LASCO and SECCHI coronagraphs. © Springer Science+Business Media B.V. 2010. 2010 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_00380938_v262_n2_p481_Goussies http://hdl.handle.net/20.500.12110/paper_00380938_v262_n2_p481_Goussies
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic Automatic tracking
CME
Coronagraph
spellingShingle Automatic tracking
CME
Coronagraph
Tracking of coronal white-light events by texture
topic_facet Automatic tracking
CME
Coronagraph
description The extraction of the kinematic properties of coronal mass ejections (CMEs) from white-light coronagraph images involves a significant degree of user interaction: defining the edge of the event, separating the core from the front or from nearby unrelated structures, etc. To contribute towards a less subjective and more quantitative definition, and therefore better kinematic characterization of such events, we have developed a novel image-processing technique based on the concept of "texture of the event". The texture is defined by the so-called gray-level co-occurrence matrix, and the technique consists of a supervised segmentation algorithm to isolate a particular region of interest based upon its similarity with a pre-specified model. Once the event is visually defined early in its evolution, it is possible to automatically track the event by applying the segmentation algorithm to the corresponding time series of coronagraph images. In this paper we describe the technique, present some examples, and show how the coronal background, the core of the event, and even the associated shock (if one exists) can be identified for different kind of CMEs detected by the LASCO and SECCHI coronagraphs. © Springer Science+Business Media B.V. 2010.
title Tracking of coronal white-light events by texture
title_short Tracking of coronal white-light events by texture
title_full Tracking of coronal white-light events by texture
title_fullStr Tracking of coronal white-light events by texture
title_full_unstemmed Tracking of coronal white-light events by texture
title_sort tracking of coronal white-light events by texture
publishDate 2010
url https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_00380938_v262_n2_p481_Goussies
http://hdl.handle.net/20.500.12110/paper_00380938_v262_n2_p481_Goussies
_version_ 1768541742536065024

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