A variance analysis of the Metropolis Light Transport algorithm
The Metropolis Light Transport algorithm is a variant of the classic Metropolis method used in statistical physics. A variance analysis of the Metropolis Light Transport algorithm is presented that bounds its variance in terms of the number of paths used and the intrinsic correlation between samples...
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| Published in: | Computers & graphics Vol. 25; no. 2; pp. 287 - 294 |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
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Elsevier Ltd
01.04.2001
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| ISSN: | 0097-8493, 1873-7684 |
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| Abstract | The Metropolis Light Transport algorithm is a variant of the classic Metropolis method used in statistical physics. A variance analysis of the Metropolis Light Transport algorithm is presented that bounds its variance in terms of the number of paths used and the intrinsic correlation between samples. It is shown that the variance of a pixel is Θ(1/
N), where
N is the number of samples for the entire image. The analysis uses basic probability, Bayes’ law, and the principle of stationary distributions. This result implies that the presence of correlation in the algorithm does not make its asymptotic time complexity worse than uncorrelated Monte Carlo methods such as path tracing. |
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| AbstractList | The Metropolis Light Transport algorithm is a variant of the classic Metropolis method used in statistical physics. A variance analysis of the Metropolis Light Transport algorithm is presented that bounds its variance in terms of the number of paths used and the intrinsic correlation between samples. It is shown that the variance of a pixel is theta (1/N), where N is the number of samples for the entire image. The analysis uses basic probability, Bayes' law, and the principle of stationary distributions. This result implies that the presence of correlation in the algorithm does not make its asymptotic time complexity worse than uncorrelated Monte Carlo methods such as path tracing. copyright 2001 Elsevier Science Ltd. The Metropolis Light Transport algorithm is a variant of the classic Metropolis method used in statistical physics. A variance analysis of the Metropolis Light Transport algorithm is presented that bounds its variance in terms of the number of paths used and the intrinsic correlation between samples. It is shown that the variance of a pixel is Θ(1/ N), where N is the number of samples for the entire image. The analysis uses basic probability, Bayes’ law, and the principle of stationary distributions. This result implies that the presence of correlation in the algorithm does not make its asymptotic time complexity worse than uncorrelated Monte Carlo methods such as path tracing. |
| Author | Ashikhmin, Michael Smits, Brian Shirley, Peter Premože, Simon |
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| Cites_doi | 10.1145/258734.258775 10.1145/192161.192179 10.1146/annurev.pc.27.100176.001535 10.1145/258734.258818 10.1063/1.1699114 |
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| Keywords | Analysis of algorithms and problem complexity Three-dimensional graphics and realism Monte Carlo raytracing Probability and statistics numerical algorithms and problems Simulation and modeling |
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| References_xml | – reference: Dutré P. Mathematical frameworks for global illumination. Ph.D. thesis, Katholieke Universiteit Leuven, 1996. – reference: Szirmay-Kalos L, Dornbach P, Purgathofer W. On the start-up bias problem of metropolis sampling. In: Skala V, editor. WSCG’99 — The Seventh International Conference in Central Europe on Computer Graphics. West Bohemia: University of West Bohemia Press. – volume: 27 start-page: 319 year: 1976 ident: BIB5 article-title: Molecular dynamics and Monte Carlo calculations in statistical mechanics publication-title: Annual Review of Physical Chemistry – year: 1999 ident: BIB9 publication-title: Monte Carlo methods in statistical physics – reference: Arvo J, Torrance K, Smits B. A framework for the analysis of error in global illumination algorithms. In: Glassner A, editor. Proceedings of SIGGRAPH ’94, Computer Graphics Proceedings, Annual Conference Series, ACM SIGGRAPH, New York: ACM Press, Orlando, Florida, July 24–29, 1994. p. 75–84. – reference: Veach E, Guibas LJ. Metropolis light transport. In: Whitted T, editor. SIGGRAPH 97 Conference Proceedings, Annual Conference Series, ACM SIGGRAPH, Reading, MA: Addison-Wesley, August 1997. p. 65–76. – volume: 21 start-page: 1087 year: 1953 ident: BIB4 article-title: Equations of state calculations by fast computing machines publication-title: Journal of Chemical Physics – year: 1995 ident: BIB7 publication-title: Probability and measure – reference: Ferwerda JA, Pattanaik SN, Shirley P, Greenberg DP. A model of visual masking for computer graphics. In: Whitted T, editor. SIGGRAPH 97 Conference Proceedings, Annual Conference Series, ACM SIGGRAPH, Reading, MA: Addison-Wesley, August 1997. p. 143–152. – year: 1986 ident: BIB8 publication-title: Monte Carlo methods – year: 1990 ident: BIB6 publication-title: Introduction to algorithms – year: 1990 ident: 10.1016/S0097-8493(00)00131-X_BIB6 – year: 1995 ident: 10.1016/S0097-8493(00)00131-X_BIB7 – ident: 10.1016/S0097-8493(00)00131-X_BIB10 – ident: 10.1016/S0097-8493(00)00131-X_BIB3 doi: 10.1145/258734.258775 – ident: 10.1016/S0097-8493(00)00131-X_BIB1 doi: 10.1145/192161.192179 – volume: 27 start-page: 319 year: 1976 ident: 10.1016/S0097-8493(00)00131-X_BIB5 article-title: Molecular dynamics and Monte Carlo calculations in statistical mechanics publication-title: Annual Review of Physical Chemistry doi: 10.1146/annurev.pc.27.100176.001535 – ident: 10.1016/S0097-8493(00)00131-X_BIB11 doi: 10.1145/258734.258818 – year: 1999 ident: 10.1016/S0097-8493(00)00131-X_BIB9 – ident: 10.1016/S0097-8493(00)00131-X_BIB2 – volume: 21 start-page: 1087 year: 1953 ident: 10.1016/S0097-8493(00)00131-X_BIB4 article-title: Equations of state calculations by fast computing machines publication-title: Journal of Chemical Physics doi: 10.1063/1.1699114 – year: 1986 ident: 10.1016/S0097-8493(00)00131-X_BIB8 |
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| Title | A variance analysis of the Metropolis Light Transport algorithm |
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