“Improved sampling for gradient-domain metropolis light transport” by Manzi, Rousselle, Kettunen, Lehtinen and Zwicker
Conference:
Type(s):
Title:
- Improved sampling for gradient-domain metropolis light transport
Session/Category Title: Light In, Light Out
Presenter(s)/Author(s):
Abstract:
We present a generalized framework for gradient-domain Metropolis rendering, and introduce three techniques to reduce sampling artifacts and variance. The first one is a heuristic weighting strategy that combines several sampling techniques to avoid outliers. The second one is an improved mapping to generate offset paths required for computing gradients. Here we leverage the properties of manifold walks in path space to cancel out singularities. Finally, the third technique introduces generalized screen space gradient kernels. This approach aligns the gradient kernels with image structures such as texture edges and geometric discontinuities to obtain sparser gradients than with the conventional gradient kernel. We implement our framework on top of an existing Metropolis sampler, and we demonstrate significant improvements in visual and numerical quality of our results compared to previous work.
References:
1. Bhat, P., Zitnick, L., Cohen, M., and Curless, B. 2010. GradientShop: A gradient-domain optimization framework for image and video filtering. ACM Trans. Graph. 29, 2, 10:1–10:14.
2. Bolin, M. R., and Meyer, G. W. 1995. A frequency based ray tracer. In Proc. ACM SIGGRAPH 95, 409–418.
3. Chen, Q., Li, D., and Tang, C.-K. 2013. Knn matting. Pattern Analysis and Machine Intelligence, IEEE Transactions on 35, 9 (Sept), 2175–2188.
4. Dammertz, H., Sewtz, D., Hanika, J., and Lensch, H. P. A. 2010. Edge-avoiding À-trous wavelet transform for fast global illumination filtering. In Proc. High Performance Graphics 2010, 67–75.
5. Dayal, A., Woolley, C., Watson, B., and Luebke, D. 2005. Adaptive frameless rendering. In Proc. Eurographics Symposium on Rendering 2005.
6. Egan, K., Tseng, Y., Holzschuch, N., Durand, F., and Ramamoorthi, R. 2009. Frequency analysis and sheared reconstruction for rendering motion blur. ACM Trans. Graph. 28, 3, 93:1–93:13.
7. Egan, K., Hecht, F., Durand, F., and Ramamoorthi, R. 2011. Frequency analysis and sheared filtering for shadow light fields of complex occluders. ACM Trans. Graph. 30, 2, 9:1–9:13.
8. Hachisuka, T., Jarosz, W., Weistroffer, R. P., Dale, K., Humphreys, G., Zwicker, M., and Jensen, H. W. 2008. Multidimensional adaptive sampling and reconstruction for ray tracing. ACM Trans. Graph. 27, 3, 33:1–33:10.
9. Hastings, W. 1970. Monte Carlo samping methods using Markov chains and their applications. Biometrika 57, 1, 97–109.Cross Ref
10. Jakob, W., and Marschner, S. 2012. Manifold exploration: A markov chain monte carlo technique for rendering scenes with difficult specular transport. ACM Trans. Graph. 31, 4 (July), 58:1–58:13.
11. Kaplanyan, A. S., Hanika, J., and Dachsbacher, C. 2014. The natural-constraint representation of the path space for efficient light transport simulation. ACM Transactions on Graphics (Proc. SIGGRAPH) 33, 4.
12. Kelemen, C., Szirmay-Kalos, L., Antal, G., and Csonka, F. 2002. A simple and robust mutation strategy for the Metropolis light transport algorithm. Comput. Graph. Forum 21, 3, 531–540.Cross Ref
13. Kollig, T., and Keller, A. 2006. Illumination in the presence of weak singularities. In Monte Carlo and Quasi-Monte Carlo Methods 2004, H. Niederreiter and D. Talay, Eds. Springer Berlin Heidelberg, 245–257.
14. Kontkanen, J., Räsänen, J., and Keller, A. 2004. Irradiance filtering for monte carlo ray tracing. In Monte Carlo and Quasi-Monte Carlo Methods 2004, Springer, 259–272.
15. Krishnan, D., Fattal, R., and Szeliski, R. 2013. Efficient preconditioning of laplacian matrices for computer graphics. ACM Trans. Graph. 32, 4 (July), 142:1–142:15.
16. Lehtinen, J., Karras, T., Laine, S., Aittala, M., Durand, F., and Aila, T. 2013. Gradient-domain metropolis light transport. ACM Trans. Graph. 32, 4 (July), 95:1–95:12.
17. Levin, A., Rav-Acha, A., and Lischinski, D. 2008. Spectral matting. IEEE Transactions on Pattern Analysis and Machine Intelligence 30, 10, 1699–1712.
18. McCool, M. D. 1999. Anisotropic diffusion for Monte Carlo noise reduction. ACM Trans. Graph. 18, 2, 171–194.
19. Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. H., and Teller, E. 1953. Equation of state calculations by fast computing machines. Journal of Chemical Physics 21, 1087–1092.Cross Ref
20. Overbeck, R., Donner, C., and Ramamoorthi, R. 2009. Adaptive wavelet rendering. ACM Trans. Graph. 28, 5, 140:1–140:12.
21. Pérez, P., Gangnet, M., and Blake, A. 2003. Poisson image editing. ACM Trans. Graph. 22, 3, 313–318.
22. Ramamoorthi, R., Mahajan, D., and Belhumeur, P. 2007. A first-order analysis of lighting, shading, and shadows. ACM Trans. Graph. 26, 1, 2:1–2:21.
23. Rousselle, F., Knaus, C., and Zwicker, M. 2011. Adaptive sampling and reconstruction using greedy error minimization. ACM Trans. Graph. 30, 6, 159:1–159:12.
24. Rousselle, F., Manzi, M., and Zwicker, M. 2013. Robust denoising using feature and color information. Computer Graphics Forum 32, 7, 121–130.Cross Ref
25. Sen, P., and Darabi, S. 2012. On filtering the noise from the random parameters in monte carlo rendering. ACM Trans. Graph. 31, 3 (June), 18:1–18:15.
26. Shi, J., and Malik, J. 2000. Normalized cuts and image segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 22, 8 (Aug.), 888–905.
27. Veach, E., and Guibas, L. J. 1995. Optimally combining sampling techniques for Monte Carlo rendering. In Proc. ACM SIGGRAPH 95, 419–428.
28. Veach, E., and Guibas, L. J. 1997. Metropolis light transport. In Proc. ACM SIGGRAPH 97, 65–76.
29. Veach, E. 1997. Robust Monte Carlo Methods for Light Transport Simulation. PhD thesis, Stanford University.
30. Walter, B., Khungurn, P., and Bala, K. 2012. Bidirectional lightcuts. ACM Trans. Graph. 31, 4 (July), 59:1–59:11.
31. Ward, G. J., and Heckbert, P. 1992. Irradiance gradients. In Proc. Eurographics Workshop on Rendering ’92.
32. Ward, G. J., Rubinstein, F. M., and Clear, R. D. 1988. A ray tracing solution for diffuse interreflection. In Computer Graphics (Proc. ACM SIGGRAPH ’88), 85–92.
