Quasi-Monte Carlo methods have become the industry standard in computer graphics. For that purpose, efficient algorithms for low discrepancy sequences are discussed. In addition, numerical pitfalls encountered in practice are revealed. We then take a look at massively parallel quasi-Monte Carlo integro-approximation for image synthesis by light transport simulation. Beyond superior uniformity, low discrepancy points may be optimized with respect to additional criteria, such as noise characteristics at low sampling rates or the quality of low-dimensional projections.

翻译：准蒙特卡洛方法已成为计算机图形学领域的行业标准。为此，本文讨论了低差异序列的高效算法，并揭示了实践中遇到的数值陷阱。随后，我们探讨了基于光传输模拟的大规模并行准蒙特卡洛积分逼近在图像合成中的应用。除了优越的均匀性之外，低差异点还可针对附加标准进行优化，例如低采样率下的噪声特性或低维投影的质量。