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A novel Monte Carlo noise reduction operator

机译:一种新颖的蒙特卡洛降噪算子

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摘要

Monte Carlo noise appears as outliers and as interpixel incoherence in a typical image rendered at low sampling density. Unfortunately, none of the previous approaches can reduce both types of noise in a unified way. In this article, we propose such a unified Monte Carlo noise reduction approach using bilateral filtering. We extended the standard bilateral filtering method and built a new local adaptive noise reduction kernel. The new operator suppresses the outliers and interpixel incoherence in a noniterative way.
机译:在以低采样密度渲染的典型图像中,蒙特卡洛噪声表现为离群值和像素间不相干性。不幸的是,以前的方法都无法以统一的方式降低两种类型的噪声。在本文中,我们提出了一种使用双边滤波的统一蒙特卡洛降噪方法。我们扩展了标准的双边滤波方法,并构建了新的局部自适应降噪内核。新算子以非迭代方式抑制离群值和像素间不连贯性。

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