Georgiev, Iliyan2015-06-302015-06-302015-06https://diglib.eg.org/handle/10.2312/12672Reproducing the interactions between light and matter in a physically accurate way can significantly improve the realistic appearance of synthetic images, however such effects can be very computationally expensive to simulate. Pressed by strict requirements on image quality and visual realism, industrial applications have recently moved away from using legacy rasterization-based rendering solutions to fully embrace physically-based Monte Carlo methods. This dramatic shift has rekindled the interest in developing new and robust light transport simulation algorithms that can efficiently handle a wide range of scenes with complex materials and lighting – a problem that we address in this thesis. State-of-the-art Monte Carlo methods solve the global illumination problem by sampling random light transport paths in the scene via ray tracing. We analyze the efficiency of these methods, devise new path sampling techniques for rendering surface and volumetric light scattering, and develop novel means of leveraging illumination coherence via path reuse. This results in several practical rendering algorithms that produce images with less noise and remain more resilient to variations in the scene configuration than existing methods. The improved efficiency of these algorithms comes from the use of new and diverse sampling techniques, each specialized for handling a different set of lighting effects. Their robustness is due to the adaptive combination of these techniques in a way that preserves their individual strengths.enrendering, light transport, global illumination, participating media, Monte Carlo integration, importance sampling, path tracing, bidirectional path tracing, photon mapping, density estimation, many-light methodsThesis