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Coronal Loop Detection
| Content Provider | Semantic Scholar |
|---|---|
| Abstract | Alexandros Asthenidis " Coronal loops are immense arches of hot gas on the surface of the Sun, thought to be jets of hot plasma flowing along in the alleys between the strong coronal magnetic fields. They are visible at Xray, ultraviolet, and whitelight wavelengths, consisting of an arch, extending upward from the photosphere for tens or hundreds of thousands of kilometres. Bright coronal loops, in the form of coronal condensations and bright spots, are common around the time of solar maximum while larger faint ones, that last days or weeks, are more typical of the quiet corona, when solar activity is low. The two ends of a loop, known as footprints, lie in regions of the photosphere of opposite magnetic polarity to each other. " (text taken from paper [3]) The interest of the study on Coronal loops lays to the fact that they are involved in many complex phenomena occurring at the sun's surface, such as the coronal mass ejections, solar flares, etc. The data obtained through the coronal loops' study are essential in gaining better knowledge of the coronal heating problem which is of major interest. The detection of the coronal loops was used to be done by hand, though the process was very time consuming and tedious. An automated method is needed in order to detect the Coronal loops in the huge dataset of the images taken by SOHO, TRACE and the other telescopes observing the Sun. Fig. 1. Pictures of coronal loops taken from TRACE [6] (NASA Small Explorer). Although, there had been lot of research [25], the overall outcome was insufficient. The images were picked with prior knowledge of containing coronal loops and also the proposed methods could not perform in noisy images or handle problems with curve discontinuities. The research of Durak et al. [1] is more consistent and closer to the needed method. Their proposed method is applicable in any image with noise or not, without any prior knowledge of the existence of coronal loop in it. The coronal loop detection consists of three main parts: the preparation part of the image, the classification of the overall image as if a loop exists and the actual detection of the coronal loops in the image. Except from statistical and regular image features some other specialized features are extracted. The additional specialized features provide more information to the classifier in order to obtain more reliable … |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://homepages.inf.ed.ac.uk/rbf/CVonline/LOCAL_COPIES/AV0910/asthenidis.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
