In many-light rendering, a variety of visual and illumination effects, including anti-aliasing, depth of field, volumetric scattering, and subsurface scattering, are combined to create a number of virtual point lights (VPLs). This is done in order to simplify computation of the resulting illumination. Naive approaches that sum the direct illumination from many VPLs are computationally expensive; scalable methods can be computed more efficiently by clustering VPLs, and then estimating their sum by sampling a small number of VPLs. Although significant speed-up has been achieved using scalable methods, clustering leads to uncontrollable errors, resulting in noise in the rendered images. In this paper, we propose a method to improve the estimation accuracy of many-light rendering involving such visual and illumination effects. We demonstrate that our method can improve the estimation accuracy by a factor of 2.3 over the previous method.

中文翻译：

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一种通过超采样估计多光渲染中的误差的方法

在多光源渲染中，各种视觉和照明效果（包括抗锯齿，景深，体积散射和次表面散射）被组合在一起，以创建许多虚拟点光源（VPL）。这样做是为了简化所得照度的计算。幼稚的方法将许多VPL的直接照明相加，在计算上很昂贵；通过对VPL进行聚类，然后通过对少量VPL进行采样来估计可伸缩方法的总和，可以更有效地计算可伸缩方法。尽管使用可伸缩方法已实现了显着的加速，但是聚类会导致无法控制的错误，从而在渲染图像中产生噪声。在本文中，我们提出一种方法来提高涉及这种视觉和照明效果的多光渲染的估计精度。