  We present a technique to adaptively bin sparse X-ray data using weighted
Voronoi tesselations (WVTs). WVT binning is a generalisation of Cappellari &
Copin's (2001) Voronoi binning algorithm, developed for integral field
spectroscopy. WVT binning is applicable to many types of data and creates
unbiased binning structures with compact bins that do not lead the eye. We
apply the algorithm to simulated data, as well as several X-ray data sets, to
create adaptively binned intensity images, hardness ratio maps and temperature
maps with constant signal-to-noise ratio per bin. We also illustrate the
separation of diffuse gas emission from contributions of unresolved point
sources in elliptical galaxies. We compare the performance of WVT binning with
other adaptive binning and adaptive smoothing techniques. We find that the CIAO
tool csmooth creates serious artefacts and advise against its use to interpret
diffuse X-ray emission.
