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Accelerating global illumination for physically-based rendering

Lighting is essential to generate realistic images using computer graphics. The computation of lighting takes into account the multitude of ways which light propagates around a virtual scene. This is termed global illumination, and is a vital part of physically-based rendering. Although providing compelling and accurate images, this is a computationally expensive process. This thesis presents several methods to improve the speed of global illumination computation, and therefore enables faster image synthesis. Global illumination can be calculated in an offline process, typically taking many minutes to hours to compute an accurate solution, or it can be approximated at interactive or real-time rates. This work proposes three methods which tackle the problem of improving the efficiency of computing global illumination. The first is an interactive method for calculating multiple-bounce global illumination on graphics hardware, which exploits the power of the graphics pipeline to create a voxelised representation of the scene through which light transport is computed. The second is an unbiased physically-based algorithm for improving the efficiency of path generation when calculating global illumination in complicated scenes. This is adaptive, and learns information about the lighting in the scene as the rendering progresses, and uses this to reduce variance in the image. In both common scenes used in graphics and situations which involve difficult light paths, this method gives a 30 - 70% boost in performance. The third method in this thesis is a sampling method which improves the efficiency of the common indoor-outdoor lighting scenario. This is done by both combining the lighting distribution with view importance, and automatically determining the important areas of the scene in which to start light paths. This gives a speed up of between three times, and two orders of magnitude, depending on scene and lighting complexity.

Identiferoai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:537744
Date January 2011
CreatorsBashford-Rogers, Thomas
PublisherUniversity of Warwick
Source SetsEthos UK
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation
Sourcehttp://wrap.warwick.ac.uk/36762/

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