基于视觉感知的光谱评估尺度

光谱颜色复现和色度精度是评价光谱重建算法准确的基础。简单而直观的评价指标对颜色复现控制是必不可少。该指标需要同时表征复现颜色的光谱差和色度差。在研究光谱匹配评估的方法基础上，提出基于颜色视觉感知的三种光谱评估指标，通过加权人眼视觉匹配函数，实现颜色光谱差与色度的评估。通过孟塞尔颜色系统的光谱数据，该论文分析与验证三种视觉加权的评估指标的有效性。通过孟塞尔颜色系统数据，这些指标在CIELab均匀色空间中分布均匀而稳定，从而证明加权算法的评估指标是既表征到颜色感知又反映出颜色的光谱相似度。实证结果表明，加权的指标可以实现同时表征实际人眼的颜色感知和颜色光谱差异。基于人眼视觉感知的评估指标解决了颜色的原始光谱和重建光谱的光谱匹配精度的定量评价问题。所提出评价指标通过一个简单而直观的数值实现对复现颜色光谱与色度评估。

Spectral Evaluation Metric Based on Human Perception

Reasonable evaluation of spectral color reproduction and chromaticity accuracy is fundamental to evaluate the accurate of spectral reconstruction algorithm. A simple and direct evaluation index is necessary to the color reproduction. This index requires to directly characterize the spectral difference and color difference for color reproduction. Based on the study of the reproduction of the accuracy evaluation on spectral matching, this paper proposes three spectral evaluation metrics based on color visual perception. These methods are weighted spectral evaluation metrics based on human visual function. The results of weighted metrics are analyzed with Munsell color system. These metrics get the uniform distribution and stability in there replication experiment, which proves that weighted metrics are accurate metrics for color spectral reconstruction, and take into account the color perception and spectral similarity. The empirical result is that the weighted metrics indicate the actual human color perception and spectral error at same time.The metrics based on human perception solve the problem of quantitative evaluation of spectral estimation accuracy of natural spectrum matching and color spectral reconstruction.The evaluation methods in this paper show simple and intuitive color spectrum reproduction accuracy.