A deconvolution-based algorithm for crowded field photometry with unknown point spread function

Abstract

A new method is presented for determining the point

spread function (PSF) of images that lack bright and isolated

stars. It is based on the same principles as the MCS image

deconvolution algorithm. It uses the

information contained in all stellar images to achieve

the double task of reconstructing the PSFs for single or multiple

exposures of the same field and to extract the photometry of

all point sources in the field of view. The use of the full

information available allows us to construct an accurate PSF. The

possibility to simultaneously consider several exposures makes it

well suited to the measurement of the

light curves of blended point sources from data that would be

very difficult or even impossible to analyse with traditional PSF

fitting techniques.

The potential of the method for the

analysis of ground-based and space-based data is tested on

artificial images and illustrated by several examples, including

HST/NICMOS images of a lensed quasar and VLT/ISAAC images of

a faint blended Mira star in the halo of the giant elliptical

galaxy NGC 5128 (Cen A).