Imaging is an important method for astronomy research.In practice,original images acquired by a telescope are often convolved and blurred by the point-spread function(PSF),which is a very unfavorable situation for man...Imaging is an important method for astronomy research.In practice,original images acquired by a telescope are often convolved and blurred by the point-spread function(PSF),which is a very unfavorable situation for many scientific studies including astronomy.This paper introduced a single equation iterative method for solving complex linear equations,and this method can deconvolute dirty images,eliminate the effects of the PSF well.With different PSFs,this algorithm shows very good results in deconvolution.Also,with a giant PSF of aperture synthesis imaging,this algorithm improves the peak signal-to-noise ratio and structural similarity of the dirty images by 41.0%and 33.9%on average.In addition,this paper proves that the algorithm can deconvolute the dirty image by making full use of the information of each pixel in the image,even if the dirty image has salt and pepper noise or even lost areas;by its excellent properties of flexible operation to a single pixel,all these bad situations can be dealt with and the image can be restored.展开更多
We use the Richardson-Lucy deconvolution algorithm to extract one-dimensional(1 D) spectra from Large Sky Area Multi-Object Fiber Spectroscopic Telescope(LAMOST) spectrum images. Compared with other deconvolution algo...We use the Richardson-Lucy deconvolution algorithm to extract one-dimensional(1 D) spectra from Large Sky Area Multi-Object Fiber Spectroscopic Telescope(LAMOST) spectrum images. Compared with other deconvolution algorithms, this algorithm is much faster. The application on a real LAMOST image illustrates that the 1 D spectrum resulting from this method has a higher signal-to-noise ratio and resolution than those extracted by the LAMOST pipeline. Furthermore, our algorithm can effectively suppress the ringings that are often present in the 1 D resulting spectra generated by other deconvolution methods.展开更多
基金supported by the National Key R&D Program of China(No.2022YFE0133700)the National Natural Science Foundation of China(NSFC,No.12273007)+4 种基金the Guizhou Provincial Excellent Young Science and Technology Talent Program(No.YQK[2023]006)the National SKA Program of China(No.2020SKA0110300)the NSFC(No.11963003)the Guizhou Provincial Basic Research Program(Natural Science)(No.ZK[2022]143)the Cultivation project of Guizhou University(No.[2020]76).
文摘Imaging is an important method for astronomy research.In practice,original images acquired by a telescope are often convolved and blurred by the point-spread function(PSF),which is a very unfavorable situation for many scientific studies including astronomy.This paper introduced a single equation iterative method for solving complex linear equations,and this method can deconvolute dirty images,eliminate the effects of the PSF well.With different PSFs,this algorithm shows very good results in deconvolution.Also,with a giant PSF of aperture synthesis imaging,this algorithm improves the peak signal-to-noise ratio and structural similarity of the dirty images by 41.0%and 33.9%on average.In addition,this paper proves that the algorithm can deconvolute the dirty image by making full use of the information of each pixel in the image,even if the dirty image has salt and pepper noise or even lost areas;by its excellent properties of flexible operation to a single pixel,all these bad situations can be dealt with and the image can be restored.
基金supported by the Joint Research Fund in Astronomy (U1531242) under cooperative agreement between the National Natural Science Foundation of China (NSFC) and Chinese Academy of Sciences (CAS)the NSFC (No. 11673036)+1 种基金the Interdiscipline Research Funds of Beijing Normal UniversityFunding for the project has been provided by the National Development and Reform Commission
文摘We use the Richardson-Lucy deconvolution algorithm to extract one-dimensional(1 D) spectra from Large Sky Area Multi-Object Fiber Spectroscopic Telescope(LAMOST) spectrum images. Compared with other deconvolution algorithms, this algorithm is much faster. The application on a real LAMOST image illustrates that the 1 D spectrum resulting from this method has a higher signal-to-noise ratio and resolution than those extracted by the LAMOST pipeline. Furthermore, our algorithm can effectively suppress the ringings that are often present in the 1 D resulting spectra generated by other deconvolution methods.
