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Practical Noise Reduction for Progressive Stochastic Ray Tracing with Perceptual Control

机译:具有感知控制的渐进随机射线追踪的实际降噪

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摘要

A proposed method reduces noise in stochastic ray tracing for interactive progressive rendering. The method accumulates high-variance light paths in a separate buffer, which is filtered by a high-quality edge-preserving filter. Then, this method adds a combination of the noisy unfiltered samples and the less noisy (but biased) filtered samples to the low-variance samples to form the final image. A novel per-pixel blending operator combines both contributions in a way that respects a user-defined threshold on perceived noise. This method can provide fast, reliable previews, even in the presence of complex features such as specular surfaces and high-frequency textures. At the same time, it's consistent in that the bias due to filtering vanishes in the limit.
机译:所提出的方法减少了用于交互式渐进式渲染的随机射线跟踪中的噪声。该方法将高方差光路累积在单独的缓冲区中,该缓冲区由高质量的边缘保留滤镜过滤。然后,此方法将低噪声样本添加有噪声的未滤波样本和低噪声(但有偏差)的滤波样本的组合,以形成最终图像。一种新颖的每像素混合运算符以尊重用户定义的感知噪声阈值的方式将这两种贡献进行组合。即使存在诸如镜面曲面和高频纹理之类的复杂特征,此方法也可以提供快速,可靠的预览。同时,这是一致的,因为过滤导致的偏差在限制中消失了。

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