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

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    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.

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