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Color Difference Evaluation for Digital Pictorial Images Using the Magnitude Estimation Method

机译:使用幅度估计法评估数字图画图像的色差

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摘要

A new set of color difference data using complex images was collected including small and large color differences. Using 13 images, 182 test images were generated to have various average lightness, chroma or hue values compared to the original images. Twenty observers estimated the overall color difference between the reference and manipulated images shown on an sRGB monitor with 250 cd/m(2) as a peak white in a dark room. The magnitude estimation technique was adopted for the visual assessment. The parametric factors of CMC(I:c), and CIEDE2000(I:c) were optimized using the color difference data set. Results showed that CIEDE2000 performs better than CMC. The best ratio for CMC(I:c) is (4:3), while (3.5:1) is the best for CIEDE2000(I:c) for overall color difference prediction. (C) 2015 Society for Imaging Science and Technology.
机译:收集了一组使用复杂图像的新色差数据,包括小色差和大色差。使用13张图像,生成了182张测试图像,与原始图像相比,它们具有各种平均亮度,色度或色相值。二十位观察者估算了在sRGB监视器上以250 cd / m(2)的sRGB监视器显示的参考图像和经处理的图像之间的总体色差,该值是在暗室中的白色峰值。视觉估计采用了幅度估计技术。使用色差数据集优化了CMC(I:c)和CIEDE2000(I:c)的参数因子。结果表明,CIEDE2000的性能优于CMC。就整体色差预测而言,CMC(I:c)的最佳比率为(4:3),而CIEDE2000(I:c)的最佳比率为(3.5:1)。 (C)2015年影像科学与技术学会。

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  • 来源
    《Journal of Imaging Science and Technology》 |2015年第1期|010503.1-010503.8|共8页
  • 作者单位

    Ulsan Natl Inst Sci & Technol, Sch Design & Human Engn, Human & Syst Engn Dept, Ulsan, South Korea;

    Ulsan Natl Inst Sci & Technol, Sch Design & Human Engn, Human & Syst Engn Dept, Ulsan, South Korea;

    Univ Leeds, Sch Design, Leeds, W Yorkshire, England;

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