How to Coadd Images.Ⅱ.Anti-aliasing and PSF Deconvolution  

作　　者：Lei Wang Huanyuan Shan Lin Nie Dezi Liu Zhaojun Yan Guoliang Li Cheng Cheng Yushan Xie Han Qu Wenwen Zheng Xi Kang 

机构地区：[1]Purple Mountain Observatory,Chinese Academy of Sciences,Nanjing 210023,China [2]National Basic Science Data Center,Beijing 100190,China [3]Zhejiang University-Purple Mountain Observatory Joint Research Center for Astronomy,Zhejiang University,Hangzhou 310030,China [4]Shanghai Astronomical Observatory,Shanghai 200030,China [5]Key Laboratory of Radio Astronomy and Technology,Chinese Academy of Sciences,Beijing 100101,China [6]University of Chinese Academy of Sciences,Beijing 100049,China [7]Department of Information Engineering,Wuhan Institute of City,Wuhan 430083,China [8]South-Westem Institute for Astronomy Research,Yunnan University,Kunming 650500,China [9]The Shanghai Key Lab for Astrophysics.Shanghai Normal University,Shanghai200234,China [10]Chinese Academy of Sciences South America Center for Astronomy,National Astronomical Observatories,CAS,Beijing 100101,China [11]CAS Key Laboratory of Optical Astronomy,National Astronomical Observatories,Chinese Academy of Sciences,Beijing 100101,China

出　　处：《Research in Astronomy and Astrophysics》2024年第4期103-113,共11页天文和天体物理学研究（英文版）

基　　金：supported by the GHfund A(202302017475);supported by the Foundation for Distinguished Young Scholars of Jiangsu Province(No.BK20140050);the National Natural Science Foundation of China(Nos.11973070,11333008,11273061,11825303,and 11673065);the China Manned Space Project with No.CMS-CSST-2021-A01,CMSCSST-2021-A03,CMS-CSST-2021-B01;the Joint Funds of the National Natural Science Foundation of China(No.U1931210);the support from Key Research Program of Frontier Sciences,CAS,grant No.ZDBS-LY-7013;Program of Shanghai Academic/Technology Research Leader;the support from the science research grants from the China Manned Space Project with CMS-CSST-2021-A04,CMS-CSST-2021-A07。

摘　　要：We have developed a novel method for co-adding multiple under-sampled images that combines the iteratively reweighted least squares and divide-and-conquer algorithms.Our approach not only allows for the anti-aliasing of the images but also enables Point-Spread Function(PSF)deconvolution,resulting in enhanced restoration of extended sources,the highest peak signal-to-noise ratio,and reduced ringing artefacts.To test our method,we conducted numerical simulations that replicated observation runs of the China Space Station Telescope/the VLT Survey Telescope(VST)and compared our results to those obtained using previous algorithms.The simulation showed that our method outperforms previous approaches in several ways,such as restoring the profile of extended sources and minimizing ringing artefacts.Additionally,because our method relies on the inherent advantages of least squares fitting,it is more versatile and does not depend on the local uniformity hypothesis for the PSF.However,the new method consumes much more computation than the other approaches.

关 键 词：methods:analytical techniques:image processing gravitational lensing:weak (ISM:)cosmic rays 

分 类 号：D66[政治法律—政治学]