Detection of point sources

Photometry of individual sources requires an initial phase of detection. The detection process can be separated into two phases: (1) preprocessing of the image, and (2) actual detection, yielding a list of discrete sources. Given a distribution of background intensities, the probabilityof intensitydeviations for light sources as a result of the background can be calculated. Setting a maximum acceptable probability defines a unique intensity, closely related to the standard deviation of the background intensity and the signal to noise (S/N) ratio of a pixel. Expressions are derived for the S/N ratio of pixels containing stars, both for isolated stars and crowded fields. A general expression for completeness of detection of sources in crowded stellar fields is derived, using the detection threshold, the distribution of intensity measurements for an initial estimated intensity, the number of pixels occupied by a single stellar image, and the stellar luminosity function obtained with a groundbased telescope. Three different kinds of preprocessing operations were applied on an image of a globular cluster core, testing the effect on source detection. Preprocessing was done through matched filtering with an estimate of the point spread function (PSF), fitting of the PSF to each point in the image, and deconvolution. As a reference for positions and intensities, an HST WFPC2 image of the same field was used. Efficiency of detection was expressed using measured completeness of detection, mapping the effect of crowding by dividing the image into six zones with varying stellar density. PSF fitting and matched filtering yielded comparable results, while deconvolution performed equally well only for the most crowded regions, but somewhat worse for the less crowded regions. Validity of the derived expressions was evaluated with the results obtained from the test images.