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Mixing Monte Carlo and progressive rendering for improved global illumination

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Abstract

In this paper, we seek to eliminate the noise caused by caustic paths during progressive Monte Carlo path tracing. We employ a filtering strategy over path space, handling each subspace using specialized derivations of path tracing and progressive photon mapping. Evaluating diffuse paths with path tracing allows the use of sample stratification over both pixels and the image as a whole, whilst sharp detailed caustics are produced using progressive photon mapping. This is an efficient, low noise progressive algorithm with vanishing bias combining the advantages of both Monte Carlo methods, and particle tracing.

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Acknowledgements

The work presented in this paper was funded by an EPSRC doctoral training grant and also EPSRC grant number EP/I031243/1. We would like to be notified about any adoption of this method into ray-tracing software since our funding council seeks to record the impact of its funded research.

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  1. Department of Computer Science, Swansea University, Swansea, SA2 8PP, UK

    Ian C. Doidge, Mark W. Jones & Benjamin Mora

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  1. Ian C. Doidge
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  2. Mark W. Jones
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  3. Benjamin Mora
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Correspondence to Ian C. Doidge.

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Doidge, I.C., Jones, M.W. & Mora, B. Mixing Monte Carlo and progressive rendering for improved global illumination. Vis Comput 28, 603–612 (2012). https://doi.org/10.1007/s00371-012-0703-2

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