Irradiance regression for efficient final gathering in global illumination

Irradiance regression for efficient final gathering in global illumination
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辐照度回归可实现全局照明中有效的最终聚集

DOI:
10.1007/s11704-014-4211-6
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发表时间:
2015-06
影响因子:
4.2
通讯作者:
Zhou Kun
Zhou Kun
中科院分区:
计算机科学3区
文献类型:
--
作者:
Huang Xuezhen;Sun Xin;Ren Zhong;Tong Xin;Guo Baining;Zhou Kun

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光子映射由于其计算效率高而被广泛应用于全局照明绘制。但其效率仍然受到限制,主要是在最终收集所需的密集采样,这是一个过程,是至关重要的,以消除低频伪影的密度估计。在本文中,我们提出了一种方法来预测最终聚集估计与直接密度估计,从而实现高质量的全局照明光子映射与高效率。我们首先采样的阴影点的一个子集的最终聚集和直接辐射亮度估计的辐照度。然后,我们使用样本作为训练集,通过回归预测其他阴影点的最终聚集的辐照度。因此,我们能够实现约三倍的整体加速比直接的最终聚集在全局照明计算相同的渲染质量。
Photon mapping is widely used for global illumination rendering because of its high computational efficiency. But its efficiency is still limited mainly by the intensive sampling required in final gathering a process that is critical for removing low frequency artifacts of density estimation. In this paper we propose a method to predict the final gathering estimation with direct density estimation thereby achieving high quality global illumination by photon mapping with high efficiency. We first sample the irradiance of a subset of shading points by both final gathering and direct radiance estimation. Then we use the samples as a training set to predict the final gathered irradiance of other shading points through regression. Consequently we are able to achieve about three times overall speedup compared with straightforward final gathering in global illumination computation with the same rendering quality.
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