Affiliation:
1. Advanced Micro Devices, Inc., Marunouchi, Tokyo, Japan
Abstract
Sampling according to a visible normal distribution function (VNDF) is often used to sample rays scattered by glossy surfaces, such as the Smith-GGX microfacet model. However, for rough reflections, existing VNDF sampling methods can generate undesirable reflection vectors occluded by the surface. Since these occluded reflection vectors must be rejected, VNDF sampling is inefficient for rough reflections. This paper introduces an unbiased method to reduce the number of rejected samples for Smith-GGX VNDF sampling. Our method limits the sampling range for a state-of-the-art VNDF sampling method that uses a spherical cap-based sampling range. By using our method, we can reduce the variance for highly rough and low-anisotropy surfaces. Since our method only modifies the spherical cap range in the existing sampling routine, it is simple and easy to implement.
Publisher
Association for Computing Machinery (ACM)
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