基于模糊聚类的大视场地基光学天文图像薄云识别与分析

Recognition and Analysis of Thin Clouds in Optical Astronomical Images of Large Field-of-View Ground-Based Telescope Based on Fuzzy Clustering

为了提高天文观测的效率,需要对夜间地基光学天文观测中薄云的识别和影响程度评估的算法进行研究。首先,分析了云对地基光学天文观测的影响和传统地基云图的算法后,选取大视场地基光学天文设备地基广角相机阵(GWAC)的图像进行研究。其次,通过GWAC图像的灰度分布等特性的对比分析,选取模糊C均值聚类(FCM)算法处理受薄云影响的GWAC图像。然后,应用FCM算法,通过重复多组实验,选定合适的聚类层次数、迭代次数和平滑因子等关键参数。最后,将FCM算法结果与传统天文学的恒星消光方法进行比较。设置平滑因子为1.5,聚类层次数为5,经过10次循环迭代计算后,FCM算法将夜晚的天空背景聚类成5个层次。层次分布结果与目测云层厚度分布相符,且与更精确的传统天文学恒星消光方法的结果也吻合。对于大视场地基光学天文图像中的薄云,FCM算法可以有效地识别并分析出其厚薄分布结构,即能对薄云的影响程度进行分级评估。此FCM算法有望结合更大视场的鱼眼镜头和CCD相机的监测设备,研发出一类自动监测和实时评估云层分布和影响程度的专用设备,提高地基光学天文观测的效率。

To enhance the efficiency of astronomical observations,studies on algorithms for recognizing and evaluating the degree of effect of thin clouds on ground-based optical astronomical observations at night are necessary.First,we select images of ground-based wide angle camera array(GWAC),a large field-of-view ground-based optical astronomical equipment,after analyzing the effects of clouds on ground-based optical astronomical observations and traditional groundbased cloud map algorithms.Then,based on the comparison of the GWAC image characteristics,such as gray-scale value distribution,we select the fuzzy C-means clustering(FCM)algorithm to process the GWAC images affected by thin clouds.Next,by repeating multiple sets of experiments,the appropriate key parameters such as the number of clustering layers,the number of iterations,and the smoothing factor are selected using the FCM algorithm.Finally,the FCM algorithm’s results are compared to those of the traditional astronomical star-extinction method.Set the smoothing factor to 1.5 and the number of clustering layers to 5,after 10 cycles of iterative calculations,the FCM algorithm clusters the night sky background into 5 layers.The results of the hierarchical distribution match the cloud thickness distribution estimated via naked eye as well as the results of the accurate traditional astronomical star-extinction method.The FCM algorithm can effectively recognize and analyze the thickness distribution structure of thin clouds in optical astronomical images from large field-of-view ground-based telescopes,allowing it to grade the effect of thin clouds.Using a larger fieldof-view fisheye lens and CCD cameras with this FCM algorithm,it is promising to develop an equipment for monitoring the distribution of thin clouds and evaluating the degree of effect in real-time,which would enhance the efficiency of ground-based optical astronomical observations.