Error Estimation for Many-light Rendering with Supersampling

Hirokazu Sakai Kosuke Nabata Shinya Yasuaki Kei Iwasaki
Wakayama University Wakayama University Wakayama University Wakayama University
Dwango CG Research

Many-light rendering unifies the computation of various visual and illumination effects, which include anti-aliasing, depth of field, volumetric scattering, and subsurface scattering, into a simple direct illumination computation from many virtual point lights (VPLs). As a naive approach that sums the direct illumination from a large number of VPLs is computationally expensive, scalable methods cluster VPLs and estimate the sum by sampling a small number of VPLs for efficient computation. Although scalable methods have achieved significant speed-ups, they cannot control the error owing to clustering, resulting in noise in the rendered images. In this paper, we propose a method to improve the estimation accuracy for many-light rendering of such visual and illumination effects. We demonstrate that our method can improve the estimation accuracy for various visual and illumination effects up to 2.3 times compared with the previous method.
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