基于RBF神经网络的色彩空间转换研究

Research on Color Space Transformation Based on RBF Neural Network

针对可变数字印刷中色彩空间转换的要求,文章提出一种基于RBF神经网络的RGB(Red,Green,Blue)→CMYK(Cyan,Magenta,Yellow,Black)色彩空间转换方法,解决了Lab色彩空间到CMYK色彩空间的非线性关系。通过研究分析RBF神经网络的原理,建立了基于RBF神经网络色彩空间转换数学模型,并在该模型下进行数据的预测与精度分析。实验结果表明,该方法实现的转换精度非常高,转换后的色偏明显减小,转换速度也很快。

Considering the color space conversion requirement in variable digital printing, a color space transformation method from RGB to CMYK base on RBF neural network was presented in this paper and it can solve the nonlinear conversion from Lab color space to CMYK color space. By the research and analysis the principle of RBF neural network, the math model of color space transformation base on RBF neural network was established, and the data forecast and precision analysis were given finally. The experimental results show that the method has obviously high transformation precision, quick speed and much less color difference after transformation. [ Ch,3 fig. 3 tab. 10 ref. ]