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How do Major Color-Difference Formulae Perform in the High Chroma Blue Region?

机译:如何在高色调蓝地区进行主要色差公式?

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The objectives of this work were to develop a comprehensive visual dataset, NCSU-B2, around the CIE high chroma blue color centre and to use the new dataset as well as the low chroma blue dataset, NCUS-B1~([1,2]), to test the performance of the major color difference formulae in this region of color space using the standardized residual sum of squares (STRESS) index, correlation coefficient (r) and Spearman Rank coefficient (p) as performance metrics. The visual differences between the 65 samples and the color center were assessed by 16 observers under highly controlled viewing and illuminaiton conditions, using AATCC Gray Scale for Color Change, in three separate sittings and a total of 3120 assessments were obtained. The results showed that CIEDE2000 exhibited relatively better performance for the NCSU-B2 dataset in comparison to other equations examined. However, none of the tested equations gave a satisfactorily low STRESS value, or high correlation coefficient (r) and Spearman Rank coefficient (p) values. For the combined blue datasets (NCSU-B1 and B2), CAM02-UCS, CAM02-SCD, DIN99d and CIEDE2000 showed the best performance.
机译:这项工作的目标是开发一个全面的Visual DataSet,NCSU-B2,在CIE高色彩蓝色中心周围,并使用新的数据集以及低色彩蓝色数据集Ncus-B1〜([1,2] ),用标准化的剩余平方和指数,相关系数(R)和Spearman等级系数(P)作为性能度量来测试主要色差在该颜色空间区域中的主要色差公式的性能。在高度受控的观察和Illuminaiton条件下,16个观察者评估了65个样品和色彩中心之间的视觉差异,使用AATCC灰度为颜色变化,在三个单独的暗处中,获得了总共3120个评估。结果表明,与所检查的其他方程相比,Ciede2000对NCSU-B2数据集具有相对更好的性能。然而,没有测试的方程没有令人满意地低应力值,或高相关系数(R)和Spearman等级系数(P)值。对于组合的蓝色数据集(NCSU-B1和B2),CAM02-UCS,CAM02-SCD,DIN99D和CIDE2000显示了最佳性能。

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