Explorable Volumetric Depth Images from Raycasting

View-dependent image-based rendering techniques have become increasingly popular as they combine the high quality of images with the explorability of interactive techniques. However, in the context of volume rendering, previous approaches suffer from various shortcomings, including the limitation to surfaces, expensive generation, and insufficient occlusion and motion parallax impairing depth perception. In this paper, we propose Volumetric Depth Images (VDI) to overcome these issues for view-dependent volume visualization by an extension of the Layered Depth Image (LDI) approach. Instead of only saving for each view ray of one camera configuration the depth and color values for a set of surfaces, as in LDIs, VDIs store so-called super segments, each consisting of a depth range as well as composited color and opacity. This compact representation is independent from the structure of the original data and can be generated by slight modification of ray casters with very low overhead. VDIs can be rendered efficiently at high quality with arbitrary camera configurations by means of proxy frustum geometry and an efficient depth ordering scheme. When viewing the scene from the initial view point, VDIs produce results identical to the original ray casting. As demonstrated by means of a prototype implementation and data from different fields, our approach can be useful for preview rendering and a-priori analysis in in-situ contexts among others.