  To maximise data output from single-shot astronomical images, the rejection
of cosmic rays is important. We present the results of a benchmark trial
comparing various cosmic ray rejection algorithms. The procedures assess
relative performances and characteristics of the processes in cosmic ray
detection, rates of false detections of true objects and the quality of image
cleaning and reconstruction. The cosmic ray rejection algorithms developed by
Rhoads (2000), van Dokkum (2001), Pych (2004) and the IRAF task xzap by
Dickinson are tested using both simulated and real data. It is found that
detection efficiency is independent of the density of cosmic rays in an image,
being more strongly affected by the density of real objects in the field. As
expected, spurious detections and alterations to real data in the cleaning
process are also significantly increased by high object densities. We find the
Rhoads' linear filtering method to produce the best performance in detection of
cosmic ray events, however, the popular van Dokkum algorithm exhibits the
highest overall performance in terms of detection and cleaning.
