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Accurate direct illumination using iterative adaptive sampling

机译:使用迭代自适应采样进行精确的直接照明

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This paper introduces a new multipass algorithm for efficiently computing direct illumination in scenes with many lights and complex occlusion. Images are first divided into 8/spl times/8 pixel blocks and for each point to be shaded within a block, a probability density function (PDF) is constructed over the lights and sampled to estimate illumination using a small number of shadow rays. Information from these samples is then aggregated at both the pixel and block level and used to optimize the PDFs for the next pass. Over multiple passes the PDFs and pixel estimates are updated until convergence. Using aggregation and feedback progressively improves the sampling and automatically exploits both visibility and spatial coherence. We also use novel extensions for efficient antialiasing. Our adaptive multipass approach computes accurate direct illumination eight times faster than prior approaches in tests on several complex scenes.
机译:本文介绍了一种新的多通道算法,可以有效地计算具有许多灯光和复杂遮挡的场景中的直接照明。首先将图像划分为8 / spl×/ 8像素块,对于块中要阴影的每个点,在光上构建概率密度函数(PDF),并对其进行采样,以使用少量阴影射线估计照明度。然后,将这些样本中的信息在像素和块级别进行汇总,并用于优化下一次扫描的PDF。通过多次传递,PDF和像素估计值将更新,直到收敛为止。逐步使用聚合和反馈可改善采样,并自动利用可见性和空间连贯性。我们还使用新颖的扩展来实现高效的抗锯齿。在多种复杂场景的测试中,我们的自适应多通道方法计算的精确直接照明比以前的方法快八倍。

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