Progressive photon mapping: A probabilistic approach
Progressive photon mapping: A probabilistic approach
复制标题
DOI：
10.1145/1966394.1966404
复制
发表时间：
2011-05
期刊：
影响因子：
--
通讯作者：
Claude Knaus;Matthias Zwicker
中科院分区：
文献类型：
--
作者：
Claude Knaus;Matthias Zwicker
在这篇文章中，我们提出了一种新的渐进光子映射的制定。与原始渐进式光子映射算法类似，我们的方法能够计算全局照明解决方案，而不会在极限范围内产生偏差，并且只使用恒定的内存量。它在大多数其他算法难以实现的情况下产生高质量的结果，例如具有真实灯具的场景，其中光源完全被折射材料包围。我们的新配方是基于概率推导。我们的方法的关键属性是，它不需要维护本地光子统计。此外，我们的推导允许任意内核的辐射估计，包括随机射线跟踪算法。最后，我们的方法是很容易适用于体积光子映射。我们将我们的算法与以前的渐进光子映射方法进行比较，结果表明，即使没有局部光子统计，我们也可以实现相同的收敛到无偏结果。
In this article we present a novel formulation of progressive photon mapping. Similar to the original progressive photon mapping algorithm, our approach is capable of computing global illumination solutions without bias in the limit, and it uses only a constant amount of memory. It produces high-quality results in situations that are difficult for most other algorithms, such as scenes with realistic light fixtures where the light sources are completely enclosed by refractive material. Our new formulation is based on a probabilistic derivation. The key property of our approach is that it does not require the maintenance of local photon statistics. In addition, our derivation allows for arbitrary kernels in the radiance estimate and includes stochastic ray tracing algorithms. Finally, our approach is readily applicable to volumetric photon mapping. We compare our algorithm to previous progressive photon mapping approaches and show that we achieve the same convergence to unbiased results, even without local photon statistics.