Optimization Techniques For ComputationallyExpens Ive Rendering Algorithms

Abstract

This thesis focuses on a group of rendering methods known by their high computational requirements. We analyse them in detail and reduce their cost using a set of conceptually different approaches.We first focus on rendering time-varying participating media. We propose a modified formulation of the rendering equation and implement several optimizations to the ray marching algorithm. Our GPU based framework can generate photo-realistic images using high dynamic range lighting at interactive rates.We also analyse two different aspects of the generation of antialiased images.The first one is targeted to rendering screen-space anti-aliasing and reducing image artifacts. We propose a real time implementation of the morphological antialiasing algorithm that is efficient to evaluate, has a moderate impact and can be easily integrated into existing pipelines.The final part of the thesis takes a radically different approach and studies the responses of the Human Visual System to motion blurred stimuli. Using psychophysical experiments, we analyse the limits with respect to the perception of temporally antialiased images.Results, both for standard sequences and stereoscopic footage, sug- gest that human observers have notable tolerance to image artifacts like strobbing, excessive blur and noise. In some cases, images ren- dered with low quality settings may be indistinguishable from a gold standard. Based on these insights, we provide examples of how render settings can be used to reduce computation times without degradation of visual quality.In summary, this thesis describes novel algorithmic optimizations as well as introduces aspects related to human perception that can be leveraged to design more efficient rendering methods.