萤火虫检测与半缓冲

K. Jeffery
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摘要

萤火虫,或噪音尖峰,是与相邻像素相比过于明亮的像素,这是蒙特卡罗光线跟踪图像中常见的人工产物。它们是由低概率事件产生的,并且会随着更多的样本的采集而在极限中得到解决。然而,这些统计异常往往远远超出了预期范围,以至于即使排除数值上的不稳定性,它们收敛的时间也是令人望而却步的。除了萤火虫会破坏渲染图像的一般问题外,它们在颜色和方差值上的差异也会给去噪解决方案带来问题。例如,Rousselle et al.[2012]提出的非局部均值滤波[Buades et al. 2005]的距离计算在方差的极端差异下不具有鲁棒性。本文讨论了去除这些萤火虫来改善渲染图像本身,并使可用的数据更均匀地用于去噪解决方案。本文假设了一种利用半缓冲和像素方差的去噪框架,如Rousselle等人[2012]和Bitterli等人[2016]提出的框架。在确定哪些像素确实包含萤火虫方面,方差提供了比颜色通道更好的数据,而半缓冲区提供了一些保证,确保检测到的萤火虫不是渲染图像中预期的高光。
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Firefly detection with half buffers
Fireflies, or noise spikes, are overly-bright pixels out of place compared to neighboring pixels, which are a common artifact in Monte Carlo ray traced images. They arise from low-probability events, and would be resolved in the limit as more samples are taken. However, these statistical anomalies are often so far out of the expected range that the time for them to converge, even barring numerical instabilities, is prohibitive. Aside from the general problem of fireflies marring a rendered image, their difference in color and variance values can cause problems for denoising solutions. For example, the distance calculation for non-local means filtering [Buades et al. 2005] presented in Rousselle et al. [2012] is not robust under extreme differences in variance. This paper addresses removing these fireflies to improve both the rendered image on its own, and making the available data more uniform for denoising solutions. This paper assumes a denoising framework that makes use of half buffers and pixel variance, such as set forth in Rousselle et al. [2012] and Bitterli et al. [2016]. The variance provides better data than the color channels for determining which pixels do contain fireflies, whereas the half buffers provide some assurance that the detected firefly is not an expected highlight in the rendered image.
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