采用查找表的超四色打印光谱色彩校正方法

为解决多光谱图像打印输出时的色彩校正问题,提出一种采用查找表进行打印光谱色彩校正的方法.首先在超四色打印机色空间规则采样并测量采样点的光谱值,将光谱值变换至一个低维空间,建立正向查找表;然后在低维光谱空间中采样,运用非线性优化技术确定采样点在打印机色空间中的映射点,根据采样点确定优化参数来提高优化精度和时间效率,建立反向查找表;最后采用高维线性插值方法,在正向和反向查找表中插值以实现打印光谱色彩校正.实验结果表明,在相同的仿真环境下,新方法与常用的建立光谱打印色彩校正模型法相比,在正向校正的色度精度和光谱精度上分别提高了40%和44%,在反向校正精度上分别提高了51%及41%,且反向校正的时间效率提高了96%.

四色打印的灰度平衡方法研究

基于色彩学理论 ,提出两种灰度平衡算法用于从三色到四色打印的转换 ,通过对样本数据的学习自动获取四色打印所需的灰度平衡关系 ,然后将这两种方法与传统的等量代替法进行了比较 ,最后 ,基于 GCR思想 ,提出一种改进的颜色分离模型用于四色打印的底色去除处理 .实验结果表明 ,与传统方法相比 ,该方法具有逼近精度高、学习能力强和所需测试的样本工作量少的优点 ,算法对不同的打印条件 (墨水、纸张等 )

A Four-color Matching Method Combining Neural Networks with Genetic Algorithm

A brief review of color matching technology and its application of printing RGB images by CMY or CMYK ink jet printers is presented, followed by an explanation to the conventional approaches that are commonly used in color matching. Then, a four color matching method combining neural network with genetic algorithm is proposed. The initial weights and thresholds of the BP neural network for RGB to CMY color conversion are optimized by the new genetic algorithm based on evolutionarily stable strategy. The fourth component K is generated by using GCR (Gray Component Replacement) concept. Simulation experiments show that it is well behaved in both accuracy and generalization performance.