“Boosting Monte-Carlo Rendering by Ray Histogram Fusion” by Delbracio, Musé, Buades, Chauvier, Phelps, et al. …

  • ©Mauricio Delbracio, Pablo Musé, Antoni Buades, Julien Chauvier, Nicholas Phelps, and Jean-Michel Morel

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Title:

    Boosting Monte-Carlo Rendering by Ray Histogram Fusion

Session/Category Title: Sampling & Spectra


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Abstract:


    This article proposes a new multiscale filter accelerating Monte Carlo renderer. Each pixel in the image is characterized by the colors of the rays that reach its surface. The proposed filter uses a statistical distance to compare with each other the ray color distributions associated with different pixels, at each scale. Based on this distance, it decides whether two pixels can share their rays or not. This simple and easily reproducible algorithm provides a psnr gain of 10 to 15 decibels, or equivalently accelerates the rendering process by using 10 to 30 times fewer samples without observable bias. The algorithm is consistent, does not assume a particular noise model, and is immediately extendable to synthetic movies. Being based on the ray color values only, it can be combined with all rendering effects.

References:


    1. Andrew Adams, Natasha Gelfand, Jennifer Dolson, and Marc Levoy. 2009. Gaussian kd-trees for fast high-dimensional filtering. ACM Trans. Graph. 28, 3, 21:1–21:12.
    2. T. W. Anderson. 1962. On the distribution of the two-sample cramervon mises criterion. Ann. Math. Statist. 33, 3, 1148–1159.
    3. T. W. Anderson and D. A. Darling. 1952. Asymptotic theory of certain goodness-of-fit criteria based on stochastic processes. Ann. Math. Statist. 23, 2, 193–212.
    4. A. Buades, B. Coll, and J. M. Morel. 2005. A review of image denoising algorithms, with a new one. SIAM J. Multiscale Model. Simul. 4, 2, 490–530.
    5. Julian Chauvier, Mauricio Delbracio, and Nicholas Phelps. 2012. A method of accelerating monte carlo renders. U.S. Patent Application, Unpublished (filing date Nov. 5, 2012). 13/668807.
    6. P. Choudhury and J. Tumblin. 2003. The trilateral filter for high contrast images and meshes. In Proceedings of the 14th Eurographics Workshop on Rendering. 186–196.
    7. Kostadin Dabov, Alessandro Foi, Vladimir Katkovnik, and Karen O. Egiazarian. 2007. Image denoising by sparse 3-d transform-domain collaborative filtering. IEEE Trans. Image Process. 16, 8, 2080–2095.
    8. Holger Dammertz, Daniel Sewtz, Johannes Hanika, and Hendrik P. A. Lensch. 2010. Edge-avoiding a-trous wavelet transform for fast global illumination filtering. In Proceedings of the Conference on High Performance Graphics (HPG’10). 67–75.
    9. Oliver Deussen, Pat Hanrahan, Bernd Lintermann, Radomír Měch, Matt Pharr, and Przemyslaw Prusinkiewicz. 1998. Realistic modeling and rendering of plant ecosystems. In Proceedings of the 25th Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH’98). ACM Press, New York, 275–286.
    10. Philip Dutré, Kavita Bala, and Philippe Bekaert. 2006. Advanced Global Illumination 2nd Ed. AK Peters.
    11. Kevin Egan, Frédo Durand, and Ravi Ramamoorthi. 2011a. Practical filtering for efficient ray-traced directional occlusion. ACM Trans. Graph. 30, 6, 180:1–180:10.
    12. Kevin Egan, Florian Hecht, Frédo Durand, and Ravi Ramamoorthi. 2011b. Frequency analysis and sheared filtering for shadow light fields of complex occluders. ACM Trans. Graph. 30, 2, 9:1–9:13.
    13. Kevin Egan, Yu-Ting Tseng, Nicolas Holzschuch, Frédo Durand, and Ravi Ramamoorthi. 2009. Frequency analysis and sheared reconstruction for rendering motion blur. ACM Trans. Graph. 28, 3, 93:1–93:13.
    14. Toshiya Hachisuka, Wojciech Jarosz, Richard Peter Weistroffer, Kevin Dale, Greg Humphreys, Matthias Zwicker, and Henrik Wann Jensen. 2008. Multidimensional adaptive sampling and reconstruction for ray tracing. ACM Trans. Graph. 27, 33:1–33:10.
    15. H. W. Jensen and N. J. Christensen. 1995. Optimizing path tracing using noise reduction filters. In Proceedings of the 3rd International Conference in Central Europe on Computer Graphics and Visualization: Winter School of Computer Graphics and Visualization (WSCG’95).
    16. Lee and Jong-Sen. 1983. Digital image smoothing and the sigma filter. Comput. Vis. Graph. Image Process. 24, 2, 255–269.
    17. James T. Kajiya. 1986. The rendering equation. SIGGRAPH Comput. Graph. 20, 143–150.
    18. Nima Khademi Kalantari and Pradeep Sen. 2013. Removing the noise in monte carlo rendering with general image denoising algorithms. Comput. Graph. Forum 32, 2.
    19. M. Lebrun, M. Colom, A. Buades, and J. Morel. 2012. Secrets of image denoising cuisine. Acta Numerica 21, 1, 475–576.
    20. Mark E. Lee and Richard A. Redner. 1990. Filtering: A note on the use of nonlinear filtering in computer graphics. IEEE Comput. Graph. Appl. 10, 23–29.
    21. Jaakko Lehtinen, Timo Aila, Jiawen Chen, Samuli Laine, and Frédo Durand. 2011. Temporal light field reconstruction for rendering distribution effects. ACM Trans. Graph. 30, 4, 55:1–55:12.
    22. Jaakko Lehtinen, Timo Aila, Samuli Laine, and Frédo Durand. 2012. Reconstructing the indirect light field for global illumination. ACM Trans. Graph. 31, 4, 51:1–51:10.
    23. Michael D. McCool. 1999. Anisotropic diffusion for monte carlo noise reduction. ACM Trans. Graph. 18, 171–194.
    24. Ryan S. Overbeck, Craig Donner, and Ravi Ramamoorthi. 2009. Adaptive wavelet rendering. ACM Trans. Graph. 28, 140:1–140:12.
    25. Sylvain Paris, Pierre Kornprobst, Jack Tumblin, and Frédo Durand. 2007. A gentle introduction to bilateral filtering and its applications. In ACM SIGGRAPH 2007 Courses. ACM Press, New York.
    26. Matt Pharr and Greg Humphreys. 2010. Physically Based Rendering, From Theory To Implementation 2nd Ed. Morgan Kaufmann.
    27. William H. Press, Saul A. Teukolsky, William T. Vetterling, and Brian P. Flannery. 2007. Numerical Recipes, The Art of Scientific Computing 3rd Ed. Cambridge University Press, New York.
    28. Fabrice Rousselle, Claude Knaus, and Matthias Zwicker. 2011. Adaptive sampling and reconstruction using greedy error minimization. ACM Trans. Graph. 30, 159:1–159:12.
    29. Fabrice Rousselle, Claude Knaus, and Matthias Zwicker. 2012. Adaptive rendering with non-local means filtering. ACM Trans. Graph. 31, 6, 195:1–195:11.
    30. Yossi Rubner, Carlo Tomasi, and Leonidas J. Guibas. 1998. A metric for distributions with applications to image databases. In Proceedings of the 6th International Conference on Computer Vision (ICCV’98). 59–66.
    31. Holly E. Rushmeier and Gregory J. Ward. 1994. Energy preserving non-linear filters. In Proceedings of the 21st Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH’94). ACM Press, New York, 131–138.
    32. Pradeep Sen and Soheil Darabi. 2012. On filtering the noise from the random parameters in monte carlo rendering. ACM Trans. Graph. 31, 3, 18:1–18:15.
    33. Peter Shirley, Timo Aila, Jonathan Cohen, Eric Enderton, Samuli Laine, David Luebke, and Morgan McGuire. 2011. A local image reconstruction algorithm for stochastic rendering. In Proceedings of ACM/SIGGRAPH Symposium on Interactive 3D Graphics and Games. ACM Press, New York, 9–13.
    34. Cyril Soler, Kartic Subr, Frédo Durand, Nicolas Holzschuch, and François Sillion. 2009. Fourier depth of field. ACM Trans. Graph. 28, 2, 18:1–18:12.
    35. M. A. Stephens. 1970. Use of the kolmogorov-smirnov, cramer-von mises and related statistics without extensive tables. J. Royal Statist. Soc. Series B 32, 1, 115–122.
    36. Eric Veach. 1997. Robust monte carlo methods for light transport simulation. Ph.D. thesis, Stanford University, Stanford, CA.
    37. Q. Xu, Y. Liu, R. Zhang, S. Bao, and R. Scopigno. 2011. Noise reduction for path traced imaging of participating media. In Proceedings of the European Signal Processing Conference (Eusipco’11).
    38. Ruifeng Xu and Sumanta N. Pattanaik. 2005. A novel monte carlo noise reduction operator. IEEE Comput. Graph. Appl. 25, 31–35.

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