光纤阵列太阳光学望远镜研究组知识库

冕环是日冕结构的重要组成部分,对冕环的尺寸及形态学的研究有助于我们更好地认识冕环的内部结构,同时也为进一步理解日冕构造、日冕活动区演化、日冕加热、日冕磁场和日冕等离子体属性等相关问题提供线索.本文以冕环的自动检测算法和基于自动检测算法的冕环宽度统计为研究目标,首先,提出了一种有效的基于匹配滤波和非锐化掩模增强的冕环自动检测算法.其次,使用所提出的算法对太阳动力学天文台(Solar Dynamics Observatory, SDO)的大气成像组件(Atmospheric Imaging Assembly, AIA)的图像和高分辨率日冕成像仪(Highresolution Coronal Imager, Hi-C)的图像中的冕环进行检测,并将检测结果与目前性能表现较优的算法——Oriented Coronal Curved Loop Tracing(OCCULT)的检测结果进行对比,以说明本文算法能检测到更多的冕环.进一步地,获得所有检测到的冕环的主轴和其局部方向,提取、计算和统计分析了它们的横切面轮廓宽度.最后,得到如下结论:(1)本文的冕环检测算法优于现存的性能较优的冕环检测算法OCCULT,因此可以进一步用于除了冕环宽度统计以外的其他与冕环相关的科学研究中;(2)与基于OCCULT算法的环宽统计结果相比,大样本统计结果更具有普适性,且证明了基于OCCULT算法的环宽统计结果对精细结构环宽样本的缺失导致其统计结果的不完整;(3)环宽统计结果进一步证明,相比于高分辨率的Hi-C, AIA/SDO的分辨率不足以分辨大部分的精细结构冕环.

Coronal loop is an important component of solar corona, and it is useful for us to study its size, morphological structure and evolution as a result of that the studies will help us to better understand the internal structure of coronal loop. In the meantime, the studies can further provide us a clue of comprehending the construction of solar corona, the evolution of solar active region, coronal heating process, coronal magnetic field and the properties of plasma of solar corona. Currently, the majority of the scientific studies associated with coronal loop just focus on small sample analyses, which is mainly due to that the advances of automated detection algorithms of coronal loop and their scientific applications lag behind the theoretical studies of coronal loop. Although, some automated detection algorithms of coronal loop have been developed, just the algorithm named as Oriented Coronal CUrved Loop Tracing (OCCULT), which has a satisfactory performance in comparison with other existing algorithms, is applied to the scientific studies associated with coronal loop. However, the algorithm, OCCULT, is not sensitive to the weak and fine coronal loops, resulting in that its detection results lack of the coronal loops with weak intensities and fine structures. Clearly, the disadvantage of OCCULT mentioned above makes its results of large sample statistical analyses incomplete. For example, in the large sample statistical analysis of the widths of cross-section profiles of coronal loops, the statistical results of OCCULT are incomplete because the coronal loops with weak intensities and fine structures cannot be detected by it. Therefore, in this paper, a more effective detection algorithm of coronal loop is developed and further applied to the large sample statistical analysis of the widths of coronal loops to obtain more complete statistical distribution of the widths of coronal loops. First of all, in this paper, the developed algorithm of automatically detecting coronal loops based on matched filtering technique and unsharp-masking enhancement is described. Secondly, the coronal loops contained in the images of Atmospheric Imaging Assembly (AIA) of Solar Dynamics Observatory (SDO) and High-resolution Coronal Imager (Hi-C) are detected by the developed algorithm, and then the detection results are compared with those of the algorithm, OCCULT, so as to indicate that the developed algorithm can detect more coronal loops, especially the coronal loops with weak intensities and fine structures. Thirdly, the local directions of the main axes of the detected coronal loops are extracted, and corresponding cross-section profiles of the coronal loops are obtained, resulting in that the widths of the coronal loops are automatically calculated and statistically analyzed. Finally, the conclusions are obtained. (1) In comparison with OCCULT, the performance of the developed algorithm is more excellent, indicating that in addition to calculating and statistically analyzing the widths of coronal loops, the developed algorithm can also be used to other scientific applications related to coronal loops. (2) In comparison with OCCULT, the large sample statistical results of the widths of coronal loops of the developed algorithm are more complete. (3) In comparison with the high resolution of Hi-C, the resolution of AIA/SDO cannot distinguish most of coronal loops with fine structures.