  Validation of the quality of pansharpening methods is a difficult task
because the reference is not directly available. In the meantime, two main
approaches have been established: validation in reduced resolution and original
resolution. In the former approach it is still not clear how the data are to be
processed to a lower resolution. Other open issues are related to the question
which resolution and measures should be used. In the latter approach the main
problem is how the appropriate measure should be selected. In the most
comparison studies the results of both approaches do not correspond, that means
in each case other methods are selected as the best ones. Thus, the developers
of the new pansharpening methods still stand in the front of dilemma: how to
perform a correct or appropriate comparison/evaluation/validation. It should be
noted, that the third approach is possible, that is to perform the comparison
of methods in a particular application with the usage of their ground truth.
But this is not always possible, because usually developers are not working
with applications. Moreover, it can be an additional computational load for a
researcher in a particular application. In this paper some of the
questions/problems raised above are approached/discussed. The following
component substitution (CS) and high pass filtering (HPF) pansharpening methods
with additive and multiplicative models and their enhancements such as haze
correction, histogram matching, usage of spectral response functions (SRF),
modulation transfer function (MTF) based lowpass filtering are investigated on
remote sensing data of WorldView-2 and WorldView-4 sensors.
