Deconvolution is used to eliminate imperfections in the point spread function,such as sidelobes caused by incomplete sampling of radio telescopes,and is a key technology for radio synthesis imaging.Modern telescopes h...Deconvolution is used to eliminate imperfections in the point spread function,such as sidelobes caused by incomplete sampling of radio telescopes,and is a key technology for radio synthesis imaging.Modern telescopes have such high sensitivities that the observed celestial images may contain both compact and diffuse emission.This essentially requires deconvolution technology to have the ability to model both.In this paper,a deconvolution algorithm based on hybrid parameterization is proposed for the rapid reconstruction of complex celestial structures.In this algorithm,scale-free parameterization is utilized to reconstruct compact emission,while multi-scale parameterization is employed to reconstruct diffuse emission.Simulated data representing Square Kilometre Array(SKA)observations with realistic celestial brightness distributions are applied to test the performance of the algorithm.Our experiments show that,compared with other state-of-the-art deconvolution algorithms,the algorithm proposed in this paper can reconstruct complex celestial structures well and provide competitive reconstruction results while greatly improving the reconstruction speed.展开更多
基金partially supported by the National Key R&D Program of China(Nos.2018YFA0404602,2018YFA0404603)the National SKA Program of China(2020SKA0110300)+4 种基金the National Natural Science Foundation of China(NSFC,Grant Nos.11963003,61572461,11790305,U1831204)the Guizhou Science&Technology Plan Project(Platform Talent No.[2017]5788 and[2017]5781)the Youth Science&Technology Talents Development Project of the Guizhou Education Department(No.KY[2018]119 and[2018]433)the Guizhou University Talent Research Fund(No.(2018)60)the“Light of West China”Programme(2017-XBQNXZ-A-008)。
文摘Deconvolution is used to eliminate imperfections in the point spread function,such as sidelobes caused by incomplete sampling of radio telescopes,and is a key technology for radio synthesis imaging.Modern telescopes have such high sensitivities that the observed celestial images may contain both compact and diffuse emission.This essentially requires deconvolution technology to have the ability to model both.In this paper,a deconvolution algorithm based on hybrid parameterization is proposed for the rapid reconstruction of complex celestial structures.In this algorithm,scale-free parameterization is utilized to reconstruct compact emission,while multi-scale parameterization is employed to reconstruct diffuse emission.Simulated data representing Square Kilometre Array(SKA)observations with realistic celestial brightness distributions are applied to test the performance of the algorithm.Our experiments show that,compared with other state-of-the-art deconvolution algorithms,the algorithm proposed in this paper can reconstruct complex celestial structures well and provide competitive reconstruction results while greatly improving the reconstruction speed.
