“Energy redistribution path tracing” by Cline, Talbot and Egbert

  • ©David Cline, Justin Talbot, and Parris Egbert




    Energy redistribution path tracing



    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.


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