间接光路重用的方差分析以及自适应采样
Variance Analysis and Adaptive Sampling for Indirect Light Path Reuse
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摘要: 在这篇文章中, 我们研究了一系列全局光照算法中间接光路重用的方差。这些方法通常包括两个步骤, 首先生成一批少量的间接光照采样, 然后这些采样被大量的重构采样进行重用。我们的分析表明, 在重构采样率高的条件下, 估计方差主要由重构采样之间的协方差构成, 而且提高重构采样的数量无法有效地降低这一协方差。我们同时发现协方差表示了间接光照采样在重构过程中被重用的程度。这一分析启发我们设计了一个指标来近似协方差, 同时用这一指标来驱动一个自适应采样方法来降低最后渲染结果的方差。我们在两个典型的方法中进行的实验支持了我们的分析和算法, 一个是间接光场重构算法, 另一个是轴对齐的间接光照滤波算法。实验和我们的分析都表明, 我们的方法可以大大减少最终渲染结果的失真。Abstract: In this paper, we study the estimation variance of a set of global illumination algorithms based on indirect light path reuse. These algorithms usually contain two passes — in the first pass, a small number of indirect light samples are generated and evaluated, and they are then reused by a large number of reconstruction samples in the second pass. Our analysis shows that the covariance of the reconstruction samples dominates the estimation variance under high reconstruction rates and increasing the reconstruction rate cannot effectively reduce the covariance. We also find that the covariance represents to what degree the indirect light samples are reused during reconstruction. This analysis motivates us to design a heuristic approximating the covariance as well as an adaptive sampling scheme based on this heuristic to reduce the rendering variance. We validate our analysis and adaptive sampling scheme in the indirect light field reconstruction algorithm and the axis-aligned filtering algorithm for indirect lighting. Experiments are in accordance with our analysis and show that rendering artifacts can be greatly reduced at a similar computational cost.