An Image-Based Modelling Approach To GPU-based Unstructured Grid Volume Rendering

Abstract

Unstructured grid volume rendering on the GPU is an ongoing research goal. The main difficulty is how to map the irregular data efficiently to the graphics hardware. Grid cells cannot be directly processed by the pipeline since polyhedral cells are not basic graphics primitives. Thus, approaches that render directly from the grid must try to overcome inherent computational bottlenecks such as cell ordering. We present a novel image-based approach that allows for flexible sample placement and an efficient mapping to graphics hardware that can leverage current trends in hardware performance. The unstructured grid is replaced by a semi-regular data structure we call the Pixel Ray Image (PRI), which consists of a pixelized projection plane and samples defined on sampling rays that intersect the grid. Each ray is interpreted as a linear spline of scalar values. The knot count is reduced by taking advantage of coherence in the sampling direction using spline simplification. The final representation is stored in a packed fashion onto 2D textures and uploaded once to texture memory prior to rendering. We detail how to perform efficient rendering utilizing shader programming and a slice-based rendering scheme that is similar to those used by hardware-accelerated rendering approaches for regular grids.