Stochastic progressive photon mapping
Stochastic progressive photon mapping
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DOI：
10.1145/1661412.1618487
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发表时间：
2009-12
期刊：
影响因子：
--
通讯作者：
T. Hachisuka;H. Jensen
中科院分区：
文献类型：
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作者：
T. Hachisuka;H. Jensen
本文介绍了渐进式光子贴图的一个简单扩展，用于模拟具有景深、运动模糊和光泽反射等效果的全局照明。渐进光子贴图是一种强大的全局照明算法，可以处理复杂的照明设置，包括镜面反射-漫反射-镜面反射路径。该算法可以计算在极限中的点处的正确的辐射值。但是，渐进式光子贴图在渲染分布式光线跟踪效果（如景深）时无效，因为它需要多个像素采样才能计算区域上的正确平均辐射值。在本文中，我们介绍了一种新的配方渐进光子映射，称为随机渐进光子映射，这使得有可能计算正确的平均辐射值的区域。关键思想是在区域内使用共享光子统计，而不是在一个点上使用孤立的光子统计。该算法很容易实现，我们的结果表明，它如何有效地处理场景的分布式光线跟踪效果，同时保持渐进光子映射的鲁棒性在复杂的照明场景。
This paper presents a simple extension of progressive photon mapping for simulating global illumination with effects such as depth-of-field, motion blur, and glossy reflections. Progressive photon mapping is a robust global illumination algorithm that can handle complex illumination settings including specular-diffuse-specular paths. The algorithm can compute the correct radiance value at a point in the limit. However, progressive photon mapping is not effective at rendering distributed ray tracing effects, such as depth-of-field, that requires multiple pixel samples in order to compute the correct average radiance value over a region. In this paper, we introduce a new formulation of progressive photon mapping, called stochastic progressive photon mapping, which makes it possible to compute the correct average radiance value for a region. The key idea is to use shared photon statistics within the region rather than isolated photon statistics at a point. The algorithm is easy to implement, and our results demonstrate how it efficiently handles scenes with distributed ray tracing effects, while maintaining the robustness of progressive photon mapping in scenes with complex lighting.