  Reducing noise caused by the instrumentation in observational data is a
crucial step in data post-processing. A method is searched for that conserves
most of the instrumental resolution and introduces as few methodical artefacts
as possible. With such a method integrated in an observation sites software
tool-chain, the resources spent for the generation of observational data will
more likely find their way into resulting scientific publications; otherwise,
for data post-processing often methods are used, which just smear out the
noise, introduce artefacts, or decrease the provided resolution in space or
time. A short review of different techniques is given here, and a non-local
averaging method is applied to Hinode magnetograms and G-band data. The
presented method fits the needs for various kinds of observational data.
