适用于大视场的快速星像匹配算法  

A Fast Catalogue Matching Algorithm for Large Field of View

作　　者：潘祖恒 方雪清 郭碧峰 陆星 彭青玉[1,2] Pan Zuheng;Fang Xueqing;Guo Bifeng;Lu Xing;Peng Qingyu(College of Information Science and Technology,Jinan University,Guangzhou 510632,China;Sino-French Joint Laboratory for Astrometry,Dynamics and Space Science,Jinan University,Guangzhou 510632,China;Department of Physics,Jinan University,Guangzhou 510632,China)

机构地区：[1]暨南大学计算机科学系,广东广州510632 [2]暨南大学中法天体测量、动力学与空间科学联合实验室,广东广州510632 [3]暨南大学物理学系,广东广州510632

出　　处：《天文研究与技术》2023年第6期549-555,共7页Astronomical Research & Technology

基　　金：国家重点研发计划(2022YFE0116800);中国载人航天工程巡天空间望远镜专项科学研究项目(CMS-CSST-2021-B08);国家自然科学基金(11873026,11273014,U1431227);暨南大学优秀本科推免生科研创新培育计划项目资助.

摘　　要：基于CCD图像的天文观测中,星像匹配是一项基本的任务。提出一种基于k-d树和k-means聚类算法的星像匹配算法,应用三角形不变性元组对相似三角形进行盲匹配,算法可以间接计算CCD图像的比例尺。三次使用k-d树优化计算,并使用k-means聚类算法对图像进行分割,提高星像匹配的精度。使用云南天文台1 m望远镜拍摄的稀疏星场和2.4 m望远镜拍摄的密集星场进行了星像匹配算法的测试。实验结果表明,该方法能较好地自适应图像比例尺的微小变化,同时提高星像匹配的精度。Stellar catalogue matching is a fundamental task in astronomical observations based on CCD images.In this paper,a stellar catalogue matching algorithm based on k-d tree and k-means clustering algorithm is proposed in Python.Triangle invariant tuples are used for blind matching of similar triangles based on Astroalign,which can indirectly calculate the scale of CCD image.In this paper,k-d tree is used for three times to optimize the calculation,and k-means clustering algorithm is used to segment the image to improve the matching precision.For testing,we match the stars with both sparse field frames taken by the 1 m telescope at Yunnan Observatory and dense field frames taken by the 2.4 m telescope at Yunnan Observatory.Our results show that the method can effectively adapt to subtle change of image scale and improve matching precision.

关 键 词：星像匹配 CCD图像 星表 K-D树 K-MEANS聚类 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]