太阳暗条自动识别方法的发展及其在MLSO Hα资料太阳活动周中的科学应用
Development of an Advanced Automated Method for Solar Filament Recognition and Its Scientific Application to a Solar Cycle of MLSO Hα Data
摘要：
提出了一种在Hα全星盘图像中自动检测和跟踪太阳暗条的方法。该程序不仅能够识别细丝并确定其属性，如位置，面积，脊柱和其他相关参数，而且还可以跟踪细丝的日常演变。该程序包括三个步骤：首先，对原始图像进行预处理，对原始图像进行校正;其次，采用Canny边缘检测方法检测细丝;最后，通过形态学算子识别细丝属性。为了测试该算法，我们将其应用于从莫纳罗亚太阳天文台（MLSO）的观测，该程序被证明是强大的和有效的。分析了1998 - 2009年MLSO获得的Hα图像，得到了一个暗条的蝴蝶图。结果表明，第23周太阳暗条纬向迁移有3种趋势：1998年至太阳活动峰年期间，太阳暗条的漂移速度较快;峰年之后，太阳暗条纬向迁移速度相对变慢。2006年之后，迁移变得发散，标志着太阳活动极小期。在第23周，约60%的纬向大于$50^{\circ}$的暗条以较高的速度向极地迁移，南北半球纬向迁移速度差异不大。
英文摘要：
We developed a method to automatically detect and trace solar filaments in Hα full-disk images. The program is able not only to recognize filaments and determine their properties, such as the position, the area, the spine, and other relevant parameters, but also to trace the daily evolution of the filaments. The program consists of three steps: First, preprocessing is applied to correct the original images; Second, the Canny edge-detection method is used to detect filaments; Third, filament properties are recognized through the morphological operators. To test the algorithm, we applied it to the observations from the Mauna Loa Solar Observatory (MLSO), and the program is demonstrated to be robust and efficient. Hα images obtained by MLSO from 1998 to 2009 are analyzed, and a butterfly diagram of filaments is obtained. It shows that the latitudinal migration of solar filaments has three trends in the Solar Cycle 23: The drift velocity was fast from 1998 to the solar maximum; After the solar maximum, it became relatively slow. After 2006, the migration became divergent, signifying the solar minimum. About 60% filaments with the latitudes larger than $50^{\circ}$ migrate towards the polar regions with relatively high velocities, and the latitudinal migrating speeds in the northern and the southern hemispheres do not differ significantly in the Solar Cycle 23.
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