https://doi.org/10.1088/1538-3873/ad2867
Hui Zhi (支挥)1,2, Jianfeng Wang (王建峰)1,2, Xiaoming Zhang (张晓明)1,2, Jiayi Ge (葛家驿)1,2,3, Xianqun Zeng (曾显群)1, Haiwen Xie (谢海闻)2,3, Jia-Qi Wang (王佳琪)1, and Xiao-Jun Jiang (姜晓军)1,2
1 CAS Key Laboratory of Optical Astronomy National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100101, People’s Republic of China
2 University of Chinese Academy of Sciences, Beijing 100049, People’s Republic of China
3 Changchun Observatory, National Astronomical Observatories, Chinese Academy of Sciences, Changchun Jilin 130117, People’s Republic of China
Abstract
Cloud cover significantly influences ground-based optical astronomical observations, with nighttime astronomy often relying on visible light all-sky cameras for cloud detection. However, existing algorithms for processing all-sky cloud images typically require extensive manual intervention, posing challenges in identifying clouds with pronounced extinction characteristics. Furthermore, there is a lack of effective means for detailed visualization of cloud cover. To address these issues, this paper proposes a method that reconstructs the cloud distribution and thickness from all-sky images through star identification and photometry. Specifically, a high-precision star coordinate to the pixel position imaging model calibration method based on the star recognition for fisheye lenses is investigated, resulting in an all-sky rms error of less than 0.87 pixels. Based on the comprehensive reference star catalog, an optimized star extraction method based on SExtractor is developed to handle the difficulty of image source detection in all-sky cloud images. The optical thickness and distribution of cloud layers is calculated through star matching and extinction measurements. Finally, contingent upon the capability of camera and catalog star density, seven cloud layer reconstruction methods are proposed based on meshing and machine learning techniques, achieving a reconstruction accuracy of up to 1
8. The processing results from real observed images indicate that the proposed method offers a straightforward calibration process and delivers excellent cloud cover extraction and reconstruction outcomes, thereby providing practical value in telescope dynamic scheduling, site characterization and the development of observation strategies.
Keywords
All-sky cameras; Cloud monitors; Calibration; Photometry; Ground-based astronomy