Importance Resampling for Global Illumination

Talbot, Justin; Cline, David; Egbert, Parris

Importance Resampling for Global Illumination

Files

139-146.pdf (3.54 MB)

Date

2005

Authors

Talbot, Justin
Cline, David
Egbert, Parris

Publisher

The Eurographics Association

Abstract

This paper develops importance resampling into a variance reduction technique for Monte Carlo integration. Importance resampling is a sample generation technique that can be used to generate more equally weighted samples for importance sampling. This can lead to significant variance reduction over standard importance sampling for common rendering problems. We show how to select the importance resampling parameters for near optimal variance reduction. We demonstrate the robustness of this technique on common global illumination problems and achieve a 10%-70% variance reduction over standard importance sampling for direct lighting. We conclude that further variance reduction could be achieved with cheaper sampling methods.

        @inproceedings{:10.2312/EGWR/EGSR05/139-146
,
booktitle = {Eurographics Symposium on Rendering (2005)
},
editor = {Kavita Bala and Philip Dutre
},
title = {{Importance Resampling for Global Illumination
}},
author = {Talbot, Justin and 
Cline, David and 
Egbert, Parris
},
year = {2005
},
publisher = {The Eurographics Association
},
ISSN = {1727-3463
},
ISBN = {3-905673-23-1
},
DOI = {/10.2312/EGWR/EGSR05/139-146
}
}