Gradient-domain path tracing
Gradient-domain path tracing
复制标题
梯度域路径追踪
DOI：
10.1145/2766997
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发表时间：
2015
期刊：
影响因子：
--
通讯作者：
Matthias Zwicker
中科院分区：
文献类型：
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作者：
M. Kettunen;Marco Manzi;M. Aittala;J. Lehtinen;F. Durand;Matthias Zwicker
我们介绍了梯度域绘制蒙特卡罗图像合成。虽然以前的梯度域大都会光传输试图在高梯度的区域分布更多的样本，相比之下，估计图像梯度也可以使用标准（非大都会）蒙特卡罗算法，而且，即使不改变样本分布，这往往会导致显着的误差减少。这大大扩展了渐变渲染的适用性。为了深入了解梯度域采样是有益的条件下，我们提出了一个频率分析，比较Monte Carlo采样的梯度，然后泊松重建传统的Monte Carlo采样。最后，我们描述了连续域路径跟踪（G-PT），一个相对简单的修改标准的路径跟踪算法，可以产生远上级的结果。
We introduce gradient-domain rendering for Monte Carlo image synthesis. While previous gradient-domain Metropolis Light Transport sought to distribute more samples in areas of high gradients, we show, in contrast, that estimating image gradients is also possible using standard (non-Metropolis) Monte Carlo algorithms, and furthermore, that even without changing the sample distribution, this often leads to significant error reduction. This broadens the applicability of gradient rendering considerably. To gain insight into the conditions under which gradient-domain sampling is beneficial, we present a frequency analysis that compares Monte Carlo sampling of gradients followed by Poisson reconstruction to traditional Monte Carlo sampling. Finally, we describe Gradient-Domain Path Tracing (G-PT), a relatively simple modification of the standard path tracing algorithm that can yield far superior results.