技术: 图像处理, 方法: 分析, 星表

天体搜索是天文数据处理流程的一个重要环节, 也是以平方公里阵列射电望远镜(Square Kilometre Array, SKA)为代表的下一代射电望远镜在面向海量数据处理中的挑战之一. 现今天体自动搜索算法、软件已日趋成熟并投入应用, 不过在自动化、兼容性等方面仍具有提升空间. 以更自动化、更适应海量数据需求的天体搜索算法研究为宗旨, 以现有算法为研究基础, 天体自动搜索软件系统得到设计和开发. 该系统包含友好的交互式用户操作界面, 具备可视化输出数据显示、兼容不同数据输入和输出并包含为实际应用服务的文件管理功能. 该系统对于大天区图以及图像集, 均能够很好地进行自动化处理. 测试结果显示, 上述方法对于天体搜索的改进有一定成效. 后续将在此基础上对该集成系统做进一步的改进开发, 以适应更多的需求.

techniques: image processing, methods: analytical, astronomical data bases: catalogs

Source detection is an important part of data processing pipeline, and it is also one of the challenges that Square Kilometre Array (SKA) and other next generation telescopes are facing with when dealing with massive data. To date, source detection algorithms have become quite mature and been applied in various data processing. Meanwhile, there are still areas such as automation that can be further improved on, and more tests are necessary for the fulfillment of the requirement of SKA data processing. The purpose of this paper is to conduct the research on source detection algorithms that are more automated and adaptive to massive data processing. Based on it, the research team has made improvements of source detection algorithm, and designed and developed a set of automated source detection software system, which is highlighted with a user-friendly interactive interface, output display function, more compatible data input and output, and improved data management. Integrating multiple functions together enables it to have good performance for automatic processing of large sky image and image sets, and the test results show that the improvements are effective. The research team will make further improvements and develop functions to meet the needs of SKA.

国家重点研发计划(2018YFA0404603), 国家自然科学基金项目(11873079、11703069), 国家自然科学基金委员会-中国科学院天文联合基金项目(U1831204)资助