Parallel Compositing of Volumetric Depth Images for Interactive Visualization of Distributed Volumes at High Frame Rates

TL;DR

This paper introduces a parallel algorithm for generating and compositing Volumetric Depth Images from distributed large volume data, enabling smooth, interactive visualization at high frame rates.

Contribution

It presents the first method for parallel generation of VDIs from distributed data, with adaptive parameter selection for efficient visualization.

Findings

Enables real-time visualization of large distributed volumes.

Achieves high frame rates with composited VDIs.

Supports remote streaming of volume data.

Abstract

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.