{"title":"Multiframe Blind Deconvolution for Object and PSF Recovery for Astronomical Imaging","authors":"J. Christou, E. Hege, S. Jefferies","doi":"10.1364/srs.1995.rwa2","DOIUrl":null,"url":null,"abstract":"Ground-based imaging of astronomical objects typically requires some form of post-processing to realize the full information content in the recorded image. The recorded image can be expressed as which is the standard expression for incoherent imaging in the absence of noise. \ni(r→) is the measured target, \no(r→) is the true object distribution, \np(r→) represents the point spread function (PSF) of the optical system, and * denotes the convolution operation. Thus, when the PSF is known, inversion of this expression will yield the object distribution. However, in many cases, the PSF is either poorly determined or unknown. Thus standard deconvolution techniques cannot be applied.","PeriodicalId":184407,"journal":{"name":"Signal Recovery and Synthesis","volume":"36 6","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Signal Recovery and Synthesis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1364/srs.1995.rwa2","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Ground-based imaging of astronomical objects typically requires some form of post-processing to realize the full information content in the recorded image. The recorded image can be expressed as which is the standard expression for incoherent imaging in the absence of noise.
i(r→) is the measured target,
o(r→) is the true object distribution,
p(r→) represents the point spread function (PSF) of the optical system, and * denotes the convolution operation. Thus, when the PSF is known, inversion of this expression will yield the object distribution. However, in many cases, the PSF is either poorly determined or unknown. Thus standard deconvolution techniques cannot be applied.