Recent Advances in Adaptive Sampling and Reconstruction for Monte Carlo Rendering

Zwicker, Matthias; Jarosz, Wojciech; Lehtinen, Jaakko; Moon, Bochang; Ramamoorthi, Ravi; Rousselle, Fabrice; Sen, Pradeep; Soler, Cyril; Yoon, Sung-Eui (2015). Recent Advances in Adaptive Sampling and Reconstruction for Monte Carlo Rendering. Computer graphics forum, 34(2), pp. 667-681. Blackwell 10.1111/cgf.12592

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Monte Carlo integration is firmly established as the basis for most practical realistic image synthesis algorithms because of its flexibility and generality. However, the visual quality of rendered images often suffers from estimator variance, which appears as visually distracting noise. Adaptive sampling and reconstruction algorithms reduce variance by controlling the sampling density and aggregating samples in a reconstruction step, possibly over large image regions. In this paper we survey recent advances in this area. We distinguish between “a priori” methods that analyze the light transport equations and derive sampling rates and reconstruction filters from this analysis, and “a posteriori” methods that apply statistical techniques to sets of samples to drive the adaptive sampling and reconstruction process. They typically estimate the errors of several reconstruction filters, and select the best filter locally to minimize error. We discuss advantages and disadvantages of recent state-of-the-art techniques, and provide visual and quantitative comparisons. Some of these techniques are proving useful in real-world applications, and we aim to provide an overview for practitioners and researchers to assess these approaches. In addition, we discuss directions for potential further improvements.

Item Type:

Journal Article (Original Article)

Division/Institute:

08 Faculty of Science > Institute of Computer Science (INF) > Computer Graphics Group (CGG)
08 Faculty of Science > Institute of Computer Science (INF)

UniBE Contributor:

Zwicker, Matthias, Rousselle, Fabrice

Subjects:

000 Computer science, knowledge & systems
500 Science > 510 Mathematics

ISSN:

0167-7055

Publisher:

Blackwell

Funders:

[4] Swiss National Science Foundation

Projects:

[UNSPECIFIED] Efficient Sampling and Reconstruction for Image Synthesis 143886

Language:

English

Submitter:

Matthias Zwicker

Date Deposited:

08 Jun 2016 13:03

Last Modified:

05 Dec 2022 14:55

Publisher DOI:

10.1111/cgf.12592

BORIS DOI:

10.7892/boris.81120

URI:

https://boris.unibe.ch/id/eprint/81120

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