Correlation-Aware Multiple Importance Sampling for Bidirectional Rendering Algorithms

Grittmann, Pascal; Georgiev, Iliyan; Slusallek, Philipp

Correlation-Aware Multiple Importance Sampling for Bidirectional Rendering Algorithms

Files

v40i2pp231-238.pdf (6.97 MB)

paper1068.zip (392.8 MB)

cgf40-2_142628_ProjektDeal.pdf (7.69 MB)

Date

2021

Authors

Grittmann, Pascal
Georgiev, Iliyan
Slusallek, Philipp

Publisher

The Eurographics Association and John Wiley & Sons Ltd.

Abstract

Combining diverse sampling techniques via multiple importance sampling (MIS) is key to achieving robustness in modern Monte Carlo light transport simulation. Many such methods additionally employ correlated path sampling to boost efficiency. Photon mapping, bidirectional path tracing, and path-reuse algorithms construct sets of paths that share a common prefix. This correlation is ignored by classical MIS heuristics, which can result in poor technique combination and noisy images.We propose a practical and robust solution to that problem. Our idea is to incorporate correlation knowledge into the balance heuristic, based on known path densities that are already required for MIS. This correlation-aware heuristic can achieve considerably lower error than the balance heuristic, while avoiding computational and memory overhead.

        @article{10.1111:cgf.142628
,
journal = {Computer Graphics Forum},
title = {{Correlation-Aware Multiple Importance Sampling for Bidirectional Rendering Algorithms
}},
author = {Grittmann, Pascal and 
Georgiev, Iliyan and 
Slusallek, Philipp
},
year = {2021
},
publisher = {The Eurographics Association and John Wiley & Sons Ltd.
},
ISSN = {1467-8659
},
DOI = {10.1111/cgf.142628
}
}