一个基于Neugebauer方程的输入图像色彩误差校正模型

A Color Error Correction Model for Input Image Based on Neugebauer Equation

色空间转换在扫描输入图像的色彩管理中具有重要作用。现行基于光学曲线分析或黑箱法的色彩管理方法难以应用于扫描输入图像 ,在分析扫描物呈色原理和扫描误差产生原因的基础上提出了一个新的色空间转换模型。随后给出了模型推导的详细步骤 :第一步 ,重新解释 Neugebauer方程和 Yule- Nielson方程参数 ,使原本只适合印刷网点的方程也适合于非印刷网点图像 ;第二步 ,对应于扫描物呈色原理 ,分单色、双色、三色逐步考察误差修正 Yule- Nielson方程。最后 ,本算法与 BP神经网络和多项式拟合算法比较 。

Color space conversion plays important role in color management of scanning image. The existing methods for color management, which are based on optical curve analyses or black-box method, do not work well when applied to scanning image. A new model of color space conversion is presented based on analyzing the color mapping principle of scanning object and the causes of color error. Then, the derivation procedures of the color correction equation are given with more details. In the first step, the parameters of Neugebauer equation and Yule-Nielson equation are reinterpreted in order to make them can be used for continuous tone image which can used only for printing dot image originally. In the second stage, according to color mapping principle of scanning object, Yule-Nielson equation is corrected taking turns of primary color error correcting, secondary color error correcting and trichrome color error correcting. Finally, the experiment results compared with the BP neural network algorithm and polynomial matching algorithm show that the new model improves color conversion accuracy effectively.