Abstract
This paper proposes a novel architecture called Grouped Photon Mapping, which combines standard photon mapping with the light-beam concept to improve the nearest-neighbor density estimation method. Based on spatial coherence, we cluster all of photons, which are deposited in the photon map, into different beam-like groups. Each group of photons is individually stored in an isolated photon map. By the distribution of the photons in each photon map, we construct a polygonal boundary to represent a beam-like illuminated area. These boundaries offer a more accurate and flexible sampling area to filter neighbor photons around the query point. In addition, by a level of detail technique, we can control the photon-count in each group to obtain a balance between biases and noise. The results of our experiments prove that our method can successfully reduce bias errors and light leakage. Especially, for complicated caustic effects through a gemstone-like object, we can render a smoother result than standard photon mapping. © 2009 Springer-Verlag.
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Chen, L. H., Tsai, T. C., & Chen, Y. S. (2010). Grouped photon mapping. Visual Computer, 26(3), 217–226. https://doi.org/10.1007/s00371-009-0397-2
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