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arXiv 1804.03320astro-ph.SR
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太阳活动的自动探测方法及其在太阳暗条统计分析中的应用

Automated Detection Methods for Solar Activities and an Application for Statistic Analysis of Solar Filament

Q. Hao, P. F. Chen, C. Fang

摘要:

随着望远镜的迅速发展,观测的时间节奏和空间分辨率都在增加。这反过来又产生了大量的数据,只有通过自动检测才能有效地搜索这些数据,以便在观测中得出感兴趣的特征。基于图像处理和机器学习技术,已经开发了许多用于太阳活动的自动检测方法和算法。在本文中,在简要回顾了一些自动化检测方法,我们描述了我们的高效和通用的太阳能灯丝自动检测方法。它不仅能够识别细丝,确定细丝的位置、面积、脊柱等特征参数,而且能够跟踪细丝的日常演变。用它处理了近三个太阳活动周的H-α观测数据,给出了一些统计结果。

英文摘要:

With the rapid development of telescopes, both temporal cadence and the spatial resolution of observations are increasing. This in turn generates vast amount of data, which can be efficiently searched only with automated detections in order to derive the features of interest in the observations. A number of automated detection methods and algorithms have been developed for solar activities, based on the image processing and machine learning techniques. In this paper, after briefly reviewing some automated detection methods, we describe our efficient and versatile automated detection method for solar filaments. It is able not only to recognize filaments, determine the features such as the position, area, spine, and other relevant parameters, but also to trace the daily evolution of the filaments. It is applied to process the full disk H-alpha data observed in nearly three solar cycles, and some statistic results are presented.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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