Mosaicing and normalisation

The tasks of mosaicing and normalisation are normally performed using the:

• MAKEMOS

program. MAKEMOS is a comprehensive program and has many capabilities. In its default mode MAKEMOS just combines images using a selected data combination method (MAKEMOS supports several methods: mean, median, trimmed mean etc. §). In this it is similar to the MAKECAL routine, but MAKEMOS makes much more efficient use of memory (it is designed to deal with datasets which may not have much overlap and which might have a very large output extent, unlike with CCD calibration data where the overlap will usually be complete).

The other capabilities of MAKEMOS are concerned with data normalisation. Normalisation is determined as two components, a scaling factor and a zero point factor. These may be controlled independently by the parameters SCALE and ZERO. So:

% makemos in='*' out=mosaic scale
% makemos in='*' out=mosaic zero
% makemos in='*' out=mosaic scale zero

would determine just scale factors, just zero points or both scale factors and zero points respectively. The option also exists to modify the data values of the input datasets so that their values are normalised (this may be combined with producing a mosaic or not using the OUT parameter). A full description of MAKEMOS is given in appendix §, some of the philosophy of its algorithms are explained in R.F. Warren-Smith, 1993, `The Calibration of Large-Field Mosaics', Proceedings of the 5th ESO/ST-ECF Data Analysis Workshop.