在跨媒体色彩再现流程中, 受色彩再现场景光源及设备呈色机理等因素的影响, 同一色彩信息在不同数字媒介之间进行传递时, 往往存在色彩传递失真现象, 该问题严重影响了现阶段影像色彩复制与传递的客观准确性。 色度校正旨在克服上述色彩失真问题, 进而提升影像色彩信息传递品质。 现有色度校正方法主要可分为色适应变换类算法以及回归校正算法两大类, 目前由于此两类方法所采用的训练样本普遍色域过小, 故其往往导致在高饱和度色彩区域色度校正误差较大。 为此, 研究提出了一种基于宽色域色彩光谱样本集的新型色度校正方法。 通过各类典型色彩光谱样本的收集与制备, 构建了具有广阔色域范围的典型色彩光谱样本集, 并在此基础上结合色域划分及色纯度寻优方法实现了现有回归校正模型建模样本的扩充与优化, 显著提升了现阶段色度校正算法的校正精度。 实验结果显示, 在各类照明组合条件下, 相比于现有色适应变换类方法以及回归校正类方法, 所提出的色度校正方法可将以CIEDE2000色差公式表示的色度校正误差降低15%左右, 对于高饱和度色彩区域其对应降幅可达40%左右。 该方法的提出, 将为未来数字影像色彩复制领域色彩再现技术的发展, 提供有效的理论与方法支撑。

In cross-media digital color imaging workflow, the colorimetric information transform among various digital medias always suffers from large transform errors, due to the difference among the lighting illuminants and the digital devices. Colorimetric correction aims at avoiding the colorimetric transform mismatch and thus improving the color transform accuracy comprehensively. Till now, two kinds of colorimetric transform methods have been proposed, which are the chromatic adaptation transform and the regression-based transform. However, since the color gamut of the training samples of such two method are both small, adopting those methods in colorimetric domain always leads to large colorimetric transform errors for the high saturated color regions. In this research, in order to reduce the large correction error in high saturated color regions, a modified colorimetric correction method basing on a wide gamut spectral dataset was proposed. The wide gamut spectral dataset was built by comprehensively collecting and producing typical spectral color samples and could provide optimal training samples for the existing regression based colorimetric correction model, with the help of gamut partition and optimal color purity choosing. By modifying the existing method with such samples, the colorimetric correction performance obviously improved. The experimental result shows that the modified colorimetric correction method performs significantly better than the existing methods and the colorimetric correction errors are successfully reduced by around 15% according to proposed method in form of CIEDE2000 color difference, while as for the high saturated color regions the reduction rate of the colorimetric correction errors approximately grows to 40%. The authors believe that the proposed method will provided effective support for the development of digital color imaging in near future.