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Unbiased sampling techniques for image synthesis

Authors:

David Kirk,

James ArvoAuthors Info & Claims

ACM SIGGRAPH Computer Graphics, Volume 25, Issue 4

Pages 153 - 156

https://doi.org/10.1145/127719.122735

Published: 01 July 1991 Publication History

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Abstract

We examine a class of adaptive sampling techniques employed in image synthesis and show that those commonly used for efficient anti-aliasing are statistically biased. This bias is dependent upon the image function being sampled as well as the strategy for determining the number of samples to use. It is most prominent in areas of high contrast and is attributable to early stages of sampling systematically favoring one extreme or the other. If the expected outcome of the entire adaptive sampling algorithm is considered, we find that the bias of the early decisions is still present in the final estimator. We propose an alternative strategy for performing adaptive sampling that is unbiased but potentially more costly. We conclude that it may not always be practical to mitigate this source of bias, but as a source of error it should be considered when high accuracy and image fidelity are a central concern.

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Cited By

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Lu HChang WHedstrom TLi T(2024)Real-Time Path Guiding Using Bounding Voxel SamplingACM Transactions on Graphics10.1145/365820343:4(1-14)Online publication date: 19-Jul-2024
https://dl.acm.org/doi/10.1145/3658203
Rath AGrittmann PHerholz SWeier PSlusallek P(2022)EARSACM Transactions on Graphics10.1145/3528223.353016841:4(1-14)Online publication date: 22-Jul-2022
https://dl.acm.org/doi/10.1145/3528223.3530168
Xie TOlano M(2021)Real-time Subsurface Control VariatesProceedings of the ACM on Computer Graphics and Interactive Techniques10.1145/34512654:1(1-18)Online publication date: 28-Apr-2021
https://dl.acm.org/doi/10.1145/3451265
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Index Terms

Unbiased sampling techniques for image synthesis
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Image and video acquisition
        3D imaging
  2. Computer graphics
    1. Animation
    2. Image manipulation
      1. Antialiasing
2. Mathematics of computing
  1. Probability and statistics
    1. Probabilistic algorithms
    2. Probabilistic reasoning algorithms
      1. Markov-chain Monte Carlo methods
      2. Sequential Monte Carlo methods

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Published In

cover image ACM SIGGRAPH Computer Graphics

ACM SIGGRAPH Computer Graphics Volume 25, Issue 4

July 1991

340 pages

ISSN:0097-8930

DOI:10.1145/127719

Editor:
Richard J. Beach
Xerox PARC, Palo Alto, CA

Issue’s Table of Contents

SIGGRAPH '91: Proceedings of the 18th annual conference on Computer graphics and interactive techniques
July 1991
393 pages
ISBN:0897914368
DOI:10.1145/122718
Chairman:
James J. Thomas
Battelle Pacific Northwest Labs., Richland, WA

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 July 1991

Published in SIGGRAPH Volume 25, Issue 4

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Cited By

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Lu HChang WHedstrom TLi T(2024)Real-Time Path Guiding Using Bounding Voxel SamplingACM Transactions on Graphics10.1145/365820343:4(1-14)Online publication date: 19-Jul-2024
https://dl.acm.org/doi/10.1145/3658203
Rath AGrittmann PHerholz SWeier PSlusallek P(2022)EARSACM Transactions on Graphics10.1145/3528223.353016841:4(1-14)Online publication date: 22-Jul-2022
https://dl.acm.org/doi/10.1145/3528223.3530168
Xie TOlano M(2021)Real-time Subsurface Control VariatesProceedings of the ACM on Computer Graphics and Interactive Techniques10.1145/34512654:1(1-18)Online publication date: 28-Apr-2021
https://dl.acm.org/doi/10.1145/3451265
Reibold FHanika JJung ADachsbacher C(2018)Selective guided sampling with complete light transport pathsACM Transactions on Graphics10.1145/3272127.327503037:6(1-14)Online publication date: 4-Dec-2018
https://dl.acm.org/doi/10.1145/3272127.3275030
Öztireli A(2016)Integration with Stochastic Point ProcessesACM Transactions on Graphics10.1145/293218635:5(1-16)Online publication date: 8-Aug-2016
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Belcour LSoler CSubr KHolzschuch NDurand F(2013)5D Covariance tracing for efficient defocus and motion blurACM Transactions on Graphics10.1145/2487228.248723932:3(1-18)Online publication date: 4-Jul-2013
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Herzog RČadík MAydčin TKim KMyszkowski KSeidel H(2012)NoRM: No-Reference Image Quality Metric for Realistic Image SynthesisComputer Graphics Forum10.1111/j.1467-8659.2012.03055.x31:2pt4(545-554)Online publication date: 1-May-2012
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Ebeida MMitchell SDavidson APatney AKnupp POwens J(2011)Efficient and good Delaunay meshes from random pointsComputer-Aided Design10.1016/j.cad.2011.08.01243:11(1506-1515)Online publication date: 1-Nov-2011
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Jensen H(2011)Importance Driven Path Tracing using the Photon MapRendering Techniques ’9510.1007/978-3-7091-9430-0_31(326-335)Online publication date: 23-Dec-2011
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Tamstorf RJensen H(2011)Adaptive Sampling and Bias Estimation in Path TracingRendering Techniques ’9710.1007/978-3-7091-6858-5_26(285-295)Online publication date: 3-Sep-2011
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