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Project

Increasing the convergence speed of psysically-based rendering algorithms in computer graphics using frequency-based combined adaptive sampling and adaptive filtering

Physically-based rendering is one of the major research topics in the field of computer graphics. It deals with the generation of photo-realistic images depicting a virtual world. Although research in this field has a history dating back more than 25 years, generating photo-realistic images efficiently is still a problem of major significance. For each pixel in the final image a light transport equation needs to be evaluated, of which the complexity depends upon the variety of global illumination phenomena in the 3D scene. This light transport equation is typically evaluated by tracing light paths through multiple reflections between light sources and the virtual camera in the 3D scene.

This research project aims at increasing the convergence speed of these physically-based rendering algorithms by proposing new combined adaptive sampling and adaptive filtering techniques, which adapt to the frequency properties of the underlying illumination signals. Based on the inherent band limits due to the scene and camera, we can robustly derive for each pixel the required number of light paths to generate during the actual rendering and the required filter size needed during post-processing.

The proposed research is an important step towards a full comprehensive model describing the variety of global illumination phenomena ubiquitous in realistic scenes, as well as towards real-time physically accurate rendering that will enable both low sampling rates and low post processing times.

Date:20 Aug 2015 →  1 Sep 2020
Keywords:Computer Graphics, Rendering
Disciplines:Applied mathematics in specific fields, Computer architecture and networks, Distributed computing, Information sciences, Information systems, Programming languages, Scientific computing, Theoretical computer science, Visual computing, Other information and computing sciences
Project type:PhD project