A method for space-variant deblurring with application to adaptive optics imaging in astronomy

TL;DR

This paper introduces a novel space-variant deblurring method for adaptive optics astronomical images, utilizing image partitioning and boundary correction to improve image quality and photometric accuracy.

Contribution

It proposes a new deblurring technique that partitions the image into isoplanatic regions and applies boundary-corrected deconvolution, validated through simulations.

Findings

Effective boundary effects correction demonstrated

Good photometric accuracy achieved in simulated images

Method implemented in IDL and available publicly

Abstract

Images from adaptive optics systems are generally affected by significant distortions of the point spread function (PSF) across the field of view, depending on the position of natural and artificial guide stars. Image reduction techniques circumventing or mitigating these effects are important tools to take full advantage of the scientific information encoded in AO images. The aim of this paper is to propose a method for the deblurring of the astronomical image, given a set of samples of the space-variant PSF. The method is based on a partitioning of the image domain into regions of isoplanatism and on applying suitable deconvolution methods with boundary effects correction to each region. The effectiveness of the boundary effects correction is proved. Moreover, the criterion for extending the disjoint sections to partially overlapping sections is validated. The method is applied to simulated images of a stellar system characterized by a spatially variable PSF. We obtain good photometric quality, and therefore good science quality, by performing aperture photometry on the deblurred images. The proposed method is implemented in IDL in the Software Package "Patch", which is available on http://www.airyproject.eu.