中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Parameterized CLEAN Deconvolution in Radio Synthesis Imaging

文献类型:期刊论文

作者Zhang, L.1; Xu, L.2; Zhang, M.3,4
刊名Publications of the Astronomical Society of the Pacific
出版日期2020-04-01
卷号132期号:1010页码:41001
关键词methods data analysis techniques image processing algorithm interferometry reconstruction implementation Astronomy & Astrophysics
ISSN号0004-6280
DOI10.1088/1538-3873/ab7345
产权排序3
文献子类Article
英文摘要This paper reviews parameterized CLEAN deconvolution, which is widely used in radio synthesis imaging to remove the effects of sidelobes from the point-spread function caused by incomplete sampling by the radio telescope array. At the same time, different forms of parameterization and components are provided, as well as methods for approximating the true sky brightness. In recent years, a large number of variants of the CLEAN algorithm have been proposed to deliver faster and better reconstruction of extended emission. The diversity of algorithms has stemmed from the need to deal with different situations as well as optimizing the previous algorithms. In this paper, these CLEAN deconvolution algorithms are classified as scale-free, multi-scale and adaptive-scale deconvolution algorithms based on their different sky-parameterization methods. In general, scale-free algorithms are more efficient when dealing with compact sources, while multi-scale and adaptive-scale algorithms are more efficient when handing extended sources. We will cover the details of these algorithms, such as how they handle the background, their parameterization and the differences between them. In particular, we discuss the latest algorithm, which has been able to efficiently handle both compact and extended sources simultaneously via the deep integration of scale-free and adaptive-scale algorithms. We also mentioned recent developments in other important deconvolution methods and compared them with CLEAN deconvolution.
URL标识查看原文
语种英语
WOS记录号WOS:000519806400001
源URL[http://ir.xao.ac.cn/handle/45760611-7/4061]  
专题星系宇宙学研究团组
通讯作者Zhang, L.
作者单位1.College of Big Data and Information Engineering, Guizhou University, Guiyang 550025, Peopleʼs Republic of China;
2.Key Laboratory of Solar Activity, National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100101, Peopleʼs Republic of China;
3.Xinjiang Astronomical Observatory, Chinese Academy of Sciences, Urumqi 830011, Peopleʼs Republic of China;
4.Key Laboratory of Radio Astronomy, Chinese Academy of Sciences, Urumqi 830011, Peopleʼs Republic of China
推荐引用方式
GB/T 7714
Zhang, L.,Xu, L.,Zhang, M.. Parameterized CLEAN Deconvolution in Radio Synthesis Imaging[J]. Publications of the Astronomical Society of the Pacific,2020,132(1010):41001.
APA Zhang, L.,Xu, L.,&Zhang, M..(2020).Parameterized CLEAN Deconvolution in Radio Synthesis Imaging.Publications of the Astronomical Society of the Pacific,132(1010),41001.
MLA Zhang, L.,et al."Parameterized CLEAN Deconvolution in Radio Synthesis Imaging".Publications of the Astronomical Society of the Pacific 132.1010(2020):41001.

入库方式: OAI收割

来源:新疆天文台

浏览0
下载0
收藏0
其他版本

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。