PMO OpenIR
Parameterized CLEAN Deconvolution in Radio Synthesis Imaging
Zhang, L.1; Xu, L.2; Zhang, M.3,4
2020-04-01
Source PublicationPUBLICATIONS OF THE ASTRONOMICAL SOCIETY OF THE PACIFIC
ISSN0004-6280
Volume132Issue:1010Pages:13
Corresponding AuthorZhang, L.(lizhang.science@gmail.com)
AbstractThis 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.
Keywordmethods data analysis techniques image processing
DOI10.1088/1538-3873/ab7345
WOS KeywordALGORITHM ; INTERFEROMETRY ; RECONSTRUCTION ; IMPLEMENTATION
Indexed BySCI
Language英语
WOS Research AreaAstronomy & Astrophysics
WOS SubjectAstronomy & Astrophysics
WOS IDWOS:000519806400001
PublisherIOP PUBLISHING LTD
Citation statistics
Document Type期刊论文
Identifierhttp://libir.pmo.ac.cn/handle/332002/36058
Collection中国科学院紫金山天文台
Corresponding AuthorZhang, L.
Affiliation1.Guizhou Univ, Coll Big Data & Informat Engn, Guiyang 550025, Peoples R China
2.Chinese Acad Sci, Key Lab Solar Act, Natl Astron Observ, Beijing 100101, Peoples R China
3.Chinese Acad Sci, Xinjiang Astron Observ, Urumqi 830011, Peoples R China
4.Chinese Acad Sci, Key Lab Radio Astron, Urumqi 830011, Peoples R China
Recommended Citation
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):13.
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),13.
MLA Zhang, L.,et al."Parameterized CLEAN Deconvolution in Radio Synthesis Imaging".PUBLICATIONS OF THE ASTRONOMICAL SOCIETY OF THE PACIFIC 132.1010(2020):13.
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