论文标题
自动化的黑子检测是视觉观察的替代
Automated Sunspot Detection as an Alternative to Visual Observations
论文作者
论文摘要
我们使用数字白光太阳图像开发了一种用于黑子检测的自动化方法，以实现类似于黑子计数中视觉绘图观测值的性能。为了正确识别到正确的孤立点，我们特别注意太阳的安静盘组成部分的准确推导，该磁盘成分被用作使用阈值识别日晒的参考。该阈值是使用自适应方法确定的，以处理在各种条件下获得的图像。为了消除观察效果，我们的方法可以在短时间内处理多个图像。我们将开发的方法应用于在三个站点捕获的数字图像，并将检测结果与视觉观察结果进行了比较。我们得出的结论是，所提出的黑子检测方法的性能与视觉观察的性能相似。这种方法可以被公共观察者和业余爱好者以及专业的观测值广泛使用，以替代黑子计数的手绘视觉观察。
We developed an automated method for sunspot detection using digital white-light solar images to achieve a performance similar to that of visual drawing observations in sunspot counting. To identify down to small, isolated spots correctly, we pay special attention to the accurate derivation of the quiet-disk component of the Sun, which is used as a reference to identify sunspots using a threshold. This threshold is determined using an adaptive method to process images obtained under various conditions. To eliminate the seeing effect, our method can process multiple images taken within a short time. We applied the developed method to digital images captured at three sites and compared the detection results with those of visual observations. We conclude that the proposed sunspot detection method has a similar performance to that of visual observation. This method can be widely used by public observatories and amateurs as well as professional observatories as an alternative to hand-drawn visual observation for sunspot counting.
