A Better Light Candidate Generation Algorithm for ReSTIR Ray Tracing Using an Acceleration Structure to Identify Relevant Lights

Bachelor Thesis (2025)
Author(s)

R.V. Gardishyan (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

C.J. Peters – Mentor (TU Delft - Computer Graphics and Visualisation)

Elmar Eisemann – Mentor (TU Delft - Computer Graphics and Visualisation)

Michael Weinmann – Mentor (TU Delft - Computer Graphics and Visualisation)

G. Smaragdakis – Graduation committee member (TU Delft - Cyber Security)

Faculty
Electrical Engineering, Mathematics and Computer Science
More Info
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Publication Year
2025
Language
English
Graduation Date
15-07-2025
Awarding Institution
Delft University of Technology
Project
['CSE3000 Research Project']
Programme
['Computer Science and Engineering']
Faculty
Electrical Engineering, Mathematics and Computer Science
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Abstract

The efficient rendering of scenes with many light sources remains one of the most challenging problems in real-time ray tracing. As the complexity of virtual environments continues to increase, with some scenes containing thousands of light sources, traditional Monte Carlo methods struggle to achieve acceptable noise levels under real-time constraints. This paper introduces a novel approach that combines Reservoir-based Spatiotemporal Importance Resampling (ReSTIR) with a specialised bounding volume hierarchy (BVH) structure to enhance light candidate generation for scenes with many light sources. The BVH-assisted candidate generation is tested on multiple scenes, resulting in a significant decrease in image noise levels measured with the root mean squared metric (RMSE), along with improved visual quality from the first frame onward, especially in scenes with numerous light sources illuminating local areas.

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