基于数码相机的光谱重构研究

由数码相机信号直接重构物体表面的光谱信息对不同照明条件下颜色的复现十分重要.基于普通商用数码相机分别摄取两种CIE标准光源D65和A下颜色样品的RGB信号,采用主元分析法(PCA)和多项式模型的结合算法进行物体表面色光谱反射比的重构研究.实验结果表明,同时应用两种光源下的RGB信号可有效提高光谱重构精度,并能较好地再现色样的同色异谱特性.     

液晶显示器颜色特征化的分段分空间模型

为了提高液晶显示器(LCD)颜色特征化精度,根据液晶显示器色品恒定性和通道独立性较差的特点,提出了分段分空间模型。该模型首先用分段二次多项式拟合单通道驱动值和三刺激值的关系,然后再根据不同RGB子空间的颜色特性加上适当的干扰项对液晶显示器进行颜色特征化。实验结果表明,在训练样本和检验样本数分别为91和512时分段分空间模型的CIELAB平均色差为1.5881,最大色差为6.0249;通过与三维查找表、Mask、S-Curve及TPC模型的比较研究,验证了当训练样本数不多时分段分空间模型的颜色预测精度最高。     

An adaptively spatial color gamut mapping algorithm

To improve the accuracy of color image reproduction from displays to printers, an adaptively spatial color gamut mapping algorithm （ASCGMA） is proposed. In this algorithm, the compression degree of out- of-reproduction-gamut color is not only related to the position of the color in CIELCH color space, but also depending on the neighborhood of the color to be mapped. The psyehophysical experiment of pair comparison is carried out to evaluate and compare this new algorithm with the HPMINDE and SGCK gamut mapping algorithms recommended by the International Commission on Illumination （CIE）. The experimental results indicate that the proposed algorithm outperforms the algorithms of HPMINDE and SGCK except for the very dark images.