We present our image processing system for the reduction of optical imaging
data from multi-chip cameras. In the framework of the Garching Bonn Deep Survey
(GaBoDS; Schirmer et al. 2003) consisting of about 20 square degrees of
high-quality data from WFI@MPG/ESO 2.2m, our group developed an imaging
pipeline for the homogeneous and efficient processing of this large data set.
Having weak gravitational lensing as the main science driver, our algorithms
are optimised to produce deep co-added mosaics from individual exposures
obtained from empty field observations. However, the modular design of our
pipeline allows an easy adaption to different scientific applications. Our
system has already been ported to a large variety of optical instruments and
its products have been used in various scientific contexts. In this paper we
give a thorough description of the algorithms used and a careful evaluation of
the accuracies reached. This concerns the removal of the instrumental
signature, the astrometric alignment, photometric calibration and the
characterisation of final co-added mosaics. In addition we give a more general
overview on the image reduction process and comment on observing strategies
where they have significant influence on the data quality.Comment: 34 pages, 33 figures; submitted to A&A main journa