Based on the seminal work on Array-RQMC methods and rank-1 lattice sequences by Pierre L'Ecuyer and collaborators, we introduce efficient deterministic algorithms for image synthesis. Enumerating a low discrepancy sequence along the Hilbert curve superimposed on the raster of pixels of an image, we achieve noise characteristics that are desirable with respect to the human visual system, especially at very low sampling rates. As compared to the state of the art, our simple algorithms neither require randomization, nor costly optimization, nor lookup tables. We analyze correlations of space-filling curves and low discrepancy sequences, and demonstrate the benefits of the new algorithms in a professional, massively parallel light transport simulation and rendering system.
翻译:根据Pierre L'Ecuyer和协作者关于Array-RQMC方法和一级拉蒂斯序列的开创性工作,我们引入了高效的图像合成确定式算法。列举在图像像素光谱上叠加的Hilbert曲线的低差异序列,我们取得了人类视觉系统所需的噪音特征,特别是在非常低的采样率方面。与技术水平相比,我们的简单算法既不需要随机化,也不需要昂贵的优化,也不需要外观表。我们分析了空间填充曲线和低差异序列的相对关系,并在专业的、大规模平行的轻型运输模拟和制式系统中展示了新算法的好处。