  We present a parallel compositing algorithm for Volumetric Depth Images
(VDIs) of large three-dimensional volume data. Large distributed volume data
are routinely produced in both numerical simulations and experiments, yet it
remains challenging to visualize them at smooth, interactive frame rates. VDIs
are view-dependent piecewise constant representations of volume data that offer
a potential solution. They are more compact and less expensive to render than
the original data. So far, however, there is no method for generating VDIs from
distributed data. We propose an algorithm that enables this by sort-last
parallel generation and compositing of VDIs with automatically chosen
content-adaptive parameters. The resulting composited VDI can then be streamed
for remote display, providing responsive visualization of large, distributed
volume data.
