Volume reconstruction and parallel rendering algorithms: a comparative analysis
Ulrich Neumann · 1993
This work focuses on two issues of concern to designers and implementers of volume-rendering applications--finding the most efficient rendering method that provides the best image possible, and efficiently parallelizing the computation on multicomputers to render images as quickly as possible. Three volume rendering methods: ray casting, splatting, and volume shearing, are compared with respect to their reconstruction accuracy and computational expense. The computational expense of the rendering methods is modeled and measured on several workstations. The most-efficient rendering method of the three is found to be splatting. Three reconstruction-filter kernels are evaluated for their accuracy. Two error measurement methods are used. The first is image-based and uses a heuristic metric for measuring the difference between rendered images and reference images. The second method is analytical and uses a scale-space measure of feature size to compute an error bound as a function of feature size and sampling density. Of the three filter kernels tested, the separable cubic filter to found to produce the most-accurate reconstruction of the volume function. Parallel volume-rendering algorithms may be classified and described by the partitioning of tasks and data within the system. A taxonomy of algorithms is presented and the members are analyzed in terms of their communication requirements. Three optimal algorithm-classes are revealed: image partitions with both static and dynamic data distributions, and object partitions with contiguous dynamic block data distributions. Through analysis and experimental tests, a 2D mesh network-topology is shown to be sufficient for scalable performance with an object-partition algorithm when the image size is kept constant. Furthermore, the network-channel bandwidth-requirement actually decreases as the problem is scaled to a larger system and volume data size. Implementations on Pixel-Planes 5 and the Touchstone Delta demonstrate and verify the scalability of object partitions. As part of these implementations, a new load balancing approach is demonstrated for object-partition algorithms.