Acceleration methods for ray tracing based global illumination

The generation of photorealistic images is one of the major topics in computer graphics. By using the principles of physical light propagation, images that are indistinguishable from real photographs can be generated. This computation, however, is a very time-consuming task. When simulating the real behavior of light, individual images can take hours to be of sufficient quality. For this reason movie production has relied on artist driven methods to generate life-like images. Only recently there has been a convergence of techniques from physically based simulation and movie production that allowed the use of these techniques in a production environment. In this thesis we advocate this convergence and develop novel algorithms to solve the problems of computing high quality photo-realistic images for complex scenes. We investigate and extend the algorithms that are used to generate such images on a computer and we contribute novel techniques that allow to perform the necessary ray-tracing based computations faster. We consider the whole image generation pipeline starting with the low level fundamentals of fast ray tracing on modern computer architectures up to algorithmic improvements on the highest level of full photo-realistic image generation systems. In particular, we develop a novel multi-branching acceleration structure for high performance ray tracing and extend the underlying data structures by software caching to further accelerate the result. We also provide a detailed analysis on the factors that influence ray tracing speed and derive strategies for significant improvements. These create the foundations for the development of a production quality global illumination rendering system. We present the system and develop several techniques that make it usable for realistic applications. The key aspect in this system is a path space partitioning method to allow for efficient handling of highly complex illumination situations as well as the handling of complex material properties. We further develop methods to improve the illumination computation from environment maps and provide a filtering technique for preview applications.