David Cline
Abstract
We present Energy Redistribution (ER) sampling as an unbiased method to solve correlated integral problems. ER sampling is a hybrid algorithm that uses Metropolis sampling-like mutation strategies in a standard Monte Carlo integration setting, rather than resorting to an intermediate probability distribution step. In the context of global illumination, we present Energy Redistribution Path Tracing (ERPT). Beginning with an inital set of light samples taken from a path tracer, ERPT uses path mutations to redistribute the energy of the samples over the image plane to reduce variance. The result is a global illumination algorithm that is conceptually simpler than Metropolis Light Transport (MLT) while retaining its most powerful feature, path mutation. We compare images generated with the new technique to standard path tracing and MLT.
Supplemental Material
- Ashikhmin, M., Premože, S., Shirley, P., and Smits, B. 2001. A Variance Analysis of the Metropolis Light Transport Algorithm. Computers and Graphics 25, 2, 287--294.Google Scholar
Cross Ref
- Cline, D., and Egbert, P. 2005. A Practical Introduction to Metropolis Light Transport. Technical Report: Department of Computer Science, Brigham Young University, 1--19.Google Scholar
- Dutré, P., Bekaert, P., and Bala, K. 2003. Advanced Global Illumination. A. K. Peters. Google ScholarDigital Library
- Jensen, H. W. 1996. Global Illumination Using Photon Maps. In Rendering Techniques '96 (Proceedings of the Seventh Eurographics Workshop on Rendering), Springer-Verlag/Wien, New York, NY, 21--30. Google ScholarDigital Library
- Kajiya, J. T. 1986. The Rendering Equation. In Computer Graphics (Proceedings of ACM SIGGRAPH 86), ACM Press, 20, 4, 143--150. Google ScholarDigital Library
- Kelemen, C., Szirmay-Kalos, L., Antal, G., and Csonka, F. 2002. A Simple and Robust Mutation Strategy for the Metropolis Light Transport Algorithm. Computer Graphics Forum 21, 3, 1--10.Google ScholarCross Ref
- Lafortune, E. P., and Willems, Y. D. 1993. Bi-directional Path Tracing. In Proceedings of the Third International Conference on Computational Graphics and Visualization Techniques (Compugraphics '93), H. P. Santo, Ed., 145--153.Google Scholar
- Lawrence, J., Rusinkiewicz, S., and Ramamoorthi, R. 2004. Efficient BRDF Importance Sampling Using a Factored Representation. ACM Transactions on Graphics 23, 3, 494--503. Google ScholarDigital Library
- Metropolis, N., Rosenbluth, A., Rosenbluth, M., Teller, A., and Teller, E. 1953. Equations of State Calculations by Fast Computing Machines. Chemical Physics 21, 1087--1091.Google Scholar
- Pauly, M., Kollig, T., and Keller, A. 2000. Metropolis Light Transport for Participating Media. In Rendering Techniques 2000 (Proceedings of the Eleventh Eurographics Workshop on Rendering), Springer Wien, New York, NY, B. Peroche and H. Rushmeier, Eds., 11--22. Google ScholarDigital Library
- Pharr, M. 2003. Chapter 9: Metropolis Sampling. In Monte Carlo Ray Tracing, SIGGRAPH 2003 Course 44, course notes.Google Scholar
- Shirley, P., Wade, B., Hubbard, P. M., Zareski, D., Walter, B., and Greenberg, D. P. 1995. Global Illumination via Density Estimation. In Rendering Techniques 1995 (Proceedings of the Sixth Eurographics Workshop on Rendering), Springer-Verlag, New York, NY, P. M. Hanrahan and W. Purgathofer, Eds., 219--230.Google Scholar
- Szirmay-Kalos, L., Dornbach, P., and Purgathofer, W. 1999. On the Startup Bias Problem of Metropolis Sampling. Technical Report: Department of Control Engineering and Information Technology, Technical University of Budapest, 1--8.Google Scholar
- Veach, E., and Guibas, L. J. 1994. Bidirectional Estimators for Light Transport. In Rendering Techniques 1994 (Proceedings of the Fifth Eurographis Workshop on rendering), 147--162.Google Scholar
- Veach, E., and Guibas, L. J. 1995. Optimally Combining Sampling Techniques for Monte Carlo Rendering. In Proceedings of ACM SIGGRAPH 1995, ACM Press, 419--428. Google ScholarDigital Library
- Veach, E., and Guibas, L. J. 1997. Metropolis Light Transport. In Proceedings of ACM SIGGRAPH 1997, ACM Press, 65--76. Google ScholarDigital Library
- Ward, G. J., Rubinstein, F. M., and Clear, R. D. 1988. A Ray Tracing Solution for Diffuse Interreflection. In Computer Graphics (Proceedings of ACM SIGGRAPH 88), ACM, 22, 4, 85--92. Google ScholarDigital Library
Index Terms
- Energy redistribution path tracing
Recommendations
Gradient-domain path tracing
We introduce gradient-domain rendering for Monte Carlo image synthesis. While previous gradient-domain Metropolis Light Transport sought to distribute more samples in areas of high gradients, we show, in contrast, that estimating image gradients is also ...
Energy redistribution path tracing
SIGGRAPH '05: ACM SIGGRAPH 2005 PapersWe present Energy Redistribution (ER) sampling as an unbiased method to solve correlated integral problems. ER sampling is a hybrid algorithm that uses Metropolis sampling-like mutation strategies in a standard Monte Carlo integration setting, rather ...
Interactive Display of Isosurfaces with Global Illumination
In many applications, volumetric data sets are examined by displaying isosurfaces, surfaces where the data, or some function of the data, takes on a given value. Interactive applications typically use local lighting models to render such surfaces. This ...
Comments