Face-based luminance matching for perceptual colormap generation

G. Kindlmann, E. Reinhard, Sarah H. Creem-Regehr
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引用次数: 100

Abstract

Most systems used for creating and displaying colormap-based visualizations are not photometrically calibrated. That is, the relationship between RGB input levels and perceived luminance is usually not known, due to variations in the monitor, hardware configuration, and the viewing environment. However, the luminance component of perceptually based colormaps should be controlled, due to the central role that luminance plays in our visual processing. We address this problem with a simple and effective method for performing luminance matching on an uncalibrated monitor. The method is akin to the minimally distinct border technique (a previous method of luminance matching used for measuring luminous efficiency), but our method relies on the brain's highly developed ability to distinguish human faces. We present a user study showing that our method produces equivalent results to the minimally distinct border technique, but with significantly improved precision. We demonstrate how results from our luminance matching method can be directly applied to create new univariate colormaps.
基于人脸的亮度匹配感知色图生成
大多数用于创建和显示基于色图的可视化的系统都没有进行光度校准。也就是说,由于显示器、硬件配置和观看环境的变化,通常不知道RGB输入水平和感知亮度之间的关系。然而,由于亮度在我们的视觉处理中起着核心作用,基于感知的颜色图的亮度成分应该受到控制。我们用一种简单有效的方法来解决这个问题,即在未校准的监视器上进行亮度匹配。该方法类似于最小明显边界技术(先前用于测量发光效率的亮度匹配方法),但我们的方法依赖于大脑高度发达的区分人脸的能力。我们提出了一个用户研究表明,我们的方法产生等效的结果,以最低限度的明显边界技术,但具有显著提高的精度。我们演示了亮度匹配方法的结果如何直接应用于创建新的单变量颜色图。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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