Authors: N Goussies G Stenborg A Vourlidas R Howard
Publish Date: 2010/01/20
Volume: 262, Issue: 2, Pages: 481-494
Abstract
The extraction of the kinematic properties of coronal mass ejections CMEs from whitelight 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 imageprocessing technique based on the concept of “texture of the event” The texture is defined by the socalled graylevel cooccurrence matrix and the technique consists of a supervised segmentation algorithm to isolate a particular region of interest based upon its similarity with a prespecified 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
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