Evaluating image quality in Monte Carlo rendered images is an important aspect of the rendering process as we often need to determine the relative quality between images computed using different algorithms and with varying amounts of computation. The use of a gold-standard, reference image, or ground truth is a common method to provide a baseline with which to compare experimental results. We show that if not chosen carefully, the quality of reference images used for image quality assessment can skew results leading to significant misreporting of error. We present an analysis of error in Monte Carlo rendered images and discuss practices to avoid or be aware of when designing an experiment.

中文翻译：

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Monte Carlo 渲染图像中报告错误的分析

评估 Monte Carlo 渲染图像中的图像质量是渲染过程的一个重要方面，因为我们经常需要确定使用不同算法和不同计算量计算的图像之间的相对质量。使用黄金标准、参考图像或地面实况是提供用于比较实验结果的基线的常用方法。我们表明，如果不仔细选择，用于图像质量评估的参考图像的质量可能会扭曲结果，导致严重的错误报告。我们对蒙特卡罗渲染图像中的错误进行了分析，并讨论了在设计实验时要避免或注意的实践。