太阳成像数据中小尺度增亮的探测和表征
Detecting and characterising small-scale brightenings in solar imaging data
摘要：
观测太阳低层大气中的小尺度增亮可以对可能的加热/热传输机制提供有价值的限制。我们提出了一种方法的检测和分析的增亮，并证明其应用于IRIS EUV时间序列图像。该方法使用带通滤波，自适应阈值和质心跟踪，并记录事件的位置，持续时间和总/最大亮度。面积、亮度和位置也被记录为它们一生中的时间函数。检测到的增亮可以随着时间的推移而碎片化或合并，因此随着时间的推移记录构成增亮事件的不同区域的数量，并且记录区域的最大数量作为事件一致性/复杂性的简单测量。在由IRIS数据的静态背景、泊松噪声和$\approx10^4$随机分布、运动的小尺度高斯亮度组成的合成数据体上进行了试验。最大亮度，总亮度，面积和持续时间遵循幂律分布，结果显示了该方法可以提取信息的范围。记录的最大亮度是最亮和最准确检测事件的可靠测量，误差为6%。面积、持续时间和速度通常被低估15%，不确定性为20- 30%。总亮度被低估了30%，不确定性为30%。将该方法应用于54.40”$\times$和55.23”FOV上19分钟的真实IRIS QS数据，得到2997个检测结果。这些中的1340个在其寿命期间至少一次保持未片段化或片段化成两个不同的区域，相当于$3.96\times10^{-4}$ arcsec $^{-2}$ s $^{-1}$的事件密度。该方法将用于未来的大规模统计分析的几个QS数据集从IRIS，其他EUV成像仪，以及H- $α$和可见光光球图像。
英文摘要：
Observations of small-scale brightenings in the low solar atmosphere can provide valuable constraints on possible heating/heat-transport mechanisms. We present a method for the detection and analysis of brightenings and demonstrate its application to IRIS EUV time-series imagery. The method uses band-pass filtering, adaptive thresholding and centroid tracking, and records an event's position, duration, and total/maximum brightness. Area, brightness, and position are also recorded as functions of time throughout their lifetime. Detected brightenings can fragment or merge over time, thus the number of distinct regions constituting a brightening event is recorded over time and the maximum number of regions are recorded as a simple measure of an event's coherence/complexity. A test is made on a synthetic datacube composed of a static background based on IRIS data, Poisson noise and $\approx10^4$ randomly-distributed, moving, small-scale Gaussian brightenings. Maximum brightness, total brightness, area, and duration follow power-law distributions and the results show the range over which the method can extract information. The recorded maximum brightness is a reliable measure for the brightest and most accurately detected events with an error of 6%. Area, duration, and speed are generally underestimated by 15% with an uncertainty of 20-30%. Total brightness is underestimated by 30% with an uncertainty of 30%. Applying this method to real IRIS QS data spanning 19 minutes over a 54.40"$\times$55.23" FOV yields 2997 detections. 1340 of these either remain un-fragmented or fragment to two distinct regions at least once during their lifetime equating to an event density of $3.96\times10^{-4}$arcsec$^{-2}$s$^{-1}$. The method will be used for a future large-scale statistical analysis of several QS data sets from IRIS, other EUV imagers, as well as H-$α$ and visible photospheric imagery.
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