Abstract
This paper introduces a new BRDF sampling method with reduced variance, which is based on a hierarchical adaptive PDF. This PDF also is based on rejection sampling with a bounded average number of trials, even in regions where the BRDF exhibits high variations. Our algorithm works in an appropiate way with both physical, analytical and measured reflectance models. Reflected directions are sampled by using importance sampling of the BRDF times the cosine term. This fact improves computation of reflected radiance when Monte-Carlo integration is used in Global Illumination.
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Montes, R., Ureña, C., García, R., Lastra, M. (2009). An Importance Sampling Method for Arbitrary BRDFs. In: Ranchordas, A., Araújo, H.J., Pereira, J.M., Braz, J. (eds) Computer Vision and Computer Graphics. Theory and Applications. VISIGRAPP 2008. Communications in Computer and Information Science, vol 24. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10226-4_4
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DOI: https://doi.org/10.1007/978-3-642-10226-4_4
Publisher Name: Springer, Berlin, Heidelberg
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