A generalized framework for interactive volumetric point-based rendering
Klaus D. Mueller, Neophytos Neophytou · 2006
Volume Visualization is the process of displaying volumetric data represented as sample points on a regular or irregular 3D grid. The data is currently produced by medical scanners such as MRI, CT, etc, and by numerical methods such as scientific simulations. Techniques that have been proposed for this purpose over the years include direct volume-rendering which seeks to capture a visual impression of the complete 3D dataset by accounting for the emission and light absorption effects of all the data elements. This technique is effective when rendering volumes of space-filling gasses or volumes composed of many micro-surfaces, such as tissue in medical datasets. We have focused our efforts on Point-Based Volume rendering and specifically on the image-aligned post-shaded splatting algorithm which was proposed as a remedy to the drawbacks of existing algorithms with special focus on image quality. In the course of this dissertation, we will follow the evolution of this algorithm through several stages of maturity. Our contributions to this algorithm include the ability to render efficient grid topologies with significant storage and rendering time gains for both 3D as well as time-varying datasets. We have also proposed a post-convolved volume rendering technique to accelerate magnified viewing. The framework has been ported to a hardware-accelerated implementation that has the ability to interactively slice point based volumes and was optimized to take full advantage of the splatting algorithm's inherent advantages for empty-space skipping and early splat elimination. Finally, we have generalized our framework for the interactive rendering of irregular datasets consisting of ellipsoidal kernels of arbitrary size and orientation. Our suggested algorithm outperforms existing hardware approaches by about an order of magnitude in terms of throughput. Different modeling approaches have been explored for encoding the data using either RBF (Radial Basis Functions) or EBF (Elliptical Basis Functions), and new methods are proposed for ongoing/future work. The final goal is a truly general point-based hardware-accelerated framework for the interactive visualization of both regular and irregular volumetric data in high-fidelity.