A method for estimating the errors in many-light rendering with supersampling
A method for estimating the errors in many-light rendering with supersampling
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DOI：
10.1007/s41095-019-0137-0
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发表时间：
2019-04
影响因子：
6.9
通讯作者：
H. Sakai;Kosuke Nabata;Shinya Yasuaki;Kei Iwasaki
中科院分区：
文献类型：
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作者：
H. Sakai;Kosuke Nabata;Shinya Yasuaki;Kei Iwasaki
在多光渲染中，将各种视觉和照明效果（包括抗锯齿、景深、体积散射和表面下散射）组合起来以创建许多虚拟点光（VPL）。这样做是为了简化所得照明的计算。对来自许多VPL的直接照明求和的简单方法在计算上是昂贵的;可缩放方法可以通过对VPL进行聚类来更有效地计算，然后通过对少量VPL进行采样来估计它们的总和。虽然使用可扩展的方法已经实现了显着的速度提升，但聚类会导致无法控制的错误，从而导致渲染图像中的噪声。在本文中，我们提出了一种方法，以提高估计精度的多光渲染，涉及这样的视觉和照明效果。我们证明，我们的方法可以提高估计精度的2.3倍，比以前的方法。
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.