预测相机颜色质量

R. Berns
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引用次数: 0

摘要

颜色质量可以通过两种方式进行测量。第一种是基于目标的,其中报告将图像数据与基于测量的色度数据进行比较的色差统计。第二种是基于测量相机传感器的光谱灵敏度,并计算它们与标准观测者的相似性,例如μ因子。进行了一项计算实验,其中为四个μ因子为0.79、0.88、0.94和0.99的相机系统渲染了各种目标的合成图像。每个相机都使用相同的目标进行了分析。尽管所有相机的轮廓颜色精度都是可以接受的,但这并不能预测独立目标的颜色精度。μ因子是一个更好的颜色质量预测因子,建议在评估文化遗产应用的相机时使用它
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predicting Camera Color Quality
Color quality can be measured two ways. The first is target based where color-difference statistics are reported comparing image data with measurement-based colorimetric data. The second is based on measuring the camera sensor’s spectral sensitivities and calculating their similarity to a standard observer, for example, μ-factor. A computational experiment was performed where synthetic images of a variety of targets were rendered for four camera systems having μ-factors of 0.79, 0.88, 0.94, and 0.99. Each camera was profiled using the same target. Although profile color accuracy was acceptable for all the cameras, this did not predict the color accuracy for independent targets. μ-factor was a better predictor of color quality and its use is recommended when evaluating cameras for cultural heritage applications
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