A Practical Evaluation of Popular Volume Rendering Algorithms

Abstract

This paper evaluates and compares four volume rendering algorithms that have become rather popular for rendering datasets described on uniform rectilinear grids: raycasting, splatting, shear-warp, and hardware-assisted 3D texture-mapping. In order to assess both the strengths and the weaknesses of these algorithms in a wide variety of scenarios, a set of real-life benchmark datasets with different characteristics was carefully selected. In the rendering, all algorithm-independent image synthesis parameters, such as viewing matrix, transfer functions, and optical model, were kept constant to enable a fair comparison of the rendering results. Both image quality and computational complexity were evaluated and compared, with the aim of providing both researchers and practitioners with guidelines on which algorithm is most suited in which scenario. Our analysis also indicates the current weakness in each algorithm's pipeline, and possible solutions to these as well as pointers for future research are offered.