  We present the results of completeness simulations for the detection of point
sources as well as redshifted elliptical and spiral galaxies in the K'-band
images of the Munich Near-Infrared Cluster Survey (MUNICS). The main focus of
this work is to quantify the selection effects introduced by threshold-based
object detection algorithms used in deep imaging surveys. Therefore, we
simulate objects obeying the well-known scaling relations between effective
radius and central surface brightness, both for de Vaucouleurs and exponential
profiles. The results of these simulations, while presented for the MUNICS
project, are applicable in a much wider context to deep optical and
near-infrared selected samples. We investigate the detection probability as
well as the reliability for recovering the true total magnitude with Kron-like
(adaptive) aperture photometry. The results are compared to the predictions of
the visibility theory of Disney and Phillipps in terms of the detection rate
and the lost-light fraction. Additionally, the effects attributable to seeing
are explored. The results show a bias against detecting high-redshifted massive
elliptical galaxies in comparison to disk galaxies with exponential profiles,
and that the measurements of the total magnitudes for intrinsically bright
elliptical galaxies are systematically too faint. Disk galaxies, in contrast,
show no significant offset in the magnitude measurement of luminous objects.
Finally we present an analytic formula to predict the completeness of
point-sources using only basic image parameters.
