Open AccessUnbiased image reconstruction as an inverse problem
Author(s) -
Pijpers F. P.
Publication year - 1999
Publication title -
monthly notices of the royal astronomical society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.058
H-Index - 383
eISSN - 1365-2966
pISSN - 0035-8711
DOI - 10.1046/j.1365-8711.1999.02680.x
Subject(s) - transformation (genetics) , physics , point spread function , image (mathematics) , function (biology) , point (geometry) , linear map , computer vision , algorithm , artificial intelligence , optics , computer science , mathematics , geometry , biochemistry , chemistry , evolutionary biology , biology , pure mathematics , gene
An unbiased method for improving the resolution of astronomical images is presented. The strategy at the core of this method is to establish a linear transformation between the recorded image and an improved image at some desirable resolution. In order to establish this transformation only the actual point spread function and a desired point spread function need be known. No image actually recorded is used in establishing the linear transformation between the recorded and improved image. This method has a number of advantages over other methods currently in use. It is not iterative, which means it is not necessary to impose any criteria, objective or otherwise, to stop the iterations. The method does not require an artificial separation of the image into ‘smooth’ and ‘point‐like’ components, and thus is unbiased with respect to the character of structures present in the image. The method produces a linear transformation between the recorded image and the deconvolved image, and therefore the propagation of pixel‐by‐pixel flux error estimates into the deconvolved image is trivial. It is explicitly constrained to preserve photometry and should be robust against random errors.