# Quantifying the Error of Light Transport Algorithms

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**Quantifying the Error of Light Transport Algorithms.** / Celarek, A.; Jakob, W.; Wimmer, M.; Lehtinen, J.

Tutkimustuotos: Lehtiartikkeli › › vertaisarvioitu

### Harvard

*Computer Graphics Forum*, Vuosikerta. 38, Nro 4, Sivut 111-121. https://doi.org/10.1111/cgf.13775

### APA

*Computer Graphics Forum*,

*38*(4), 111-121. https://doi.org/10.1111/cgf.13775

### Vancouver

### Author

### Bibtex - Lataa

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### RIS - Lataa

TY - JOUR

T1 - Quantifying the Error of Light Transport Algorithms

AU - Celarek, A.

AU - Jakob, W.

AU - Wimmer, M.

AU - Lehtinen, J.

PY - 2019/7/1

Y1 - 2019/7/1

N2 - This paper proposes a new methodology for measuring the error of unbiased physically based rendering algorithms. The current state of the art includes mean squared error (MSE) based metrics and visual comparisons of equal-time renderings of competing algorithms. Neither is satisfying as MSE does not describe behavior and can exhibit significant variance, and visual comparisons are inherently subjective. Our contribution is two-fold: First, we propose to compute many short renderings instead of a single long run and use the short renderings to estimate MSE expectation and variance as well as per-pixel standard deviation. An algorithm that achieves good results in most runs, but with occasional outliers is essentially unreliable, which we wish to quantify numerically. We use per-pixel standard deviation to identify problematic lighting effects of rendering algorithms. The second contribution is the error spectrum ensemble (ESE), a tool for measuring the distribution of error over frequencies. The ESE serves two purposes: It reveals correlation between pixels and can be used to detect outliers, which offset the amount of error substantially.

AB - This paper proposes a new methodology for measuring the error of unbiased physically based rendering algorithms. The current state of the art includes mean squared error (MSE) based metrics and visual comparisons of equal-time renderings of competing algorithms. Neither is satisfying as MSE does not describe behavior and can exhibit significant variance, and visual comparisons are inherently subjective. Our contribution is two-fold: First, we propose to compute many short renderings instead of a single long run and use the short renderings to estimate MSE expectation and variance as well as per-pixel standard deviation. An algorithm that achieves good results in most runs, but with occasional outliers is essentially unreliable, which we wish to quantify numerically. We use per-pixel standard deviation to identify problematic lighting effects of rendering algorithms. The second contribution is the error spectrum ensemble (ESE), a tool for measuring the distribution of error over frequencies. The ESE serves two purposes: It reveals correlation between pixels and can be used to detect outliers, which offset the amount of error substantially.

KW - CCS Concepts

KW - • Computing methodologies → Ray tracing

UR - http://www.scopus.com/inward/record.url?scp=85070100686&partnerID=8YFLogxK

U2 - 10.1111/cgf.13775

DO - 10.1111/cgf.13775

M3 - Article

AN - SCOPUS:85070100686

VL - 38

SP - 111

EP - 121

JO - Computer Graphics Forum

JF - Computer Graphics Forum

SN - 0167-7055

IS - 4

ER -

ID: 38732156