【摘要】 以RGB与CIEL*a*b*颜色空间转换为例,采用径向基函数(RBF)神经网络,研究了颜色值在不同颜色空间之间的转换。利用基本采样数据集建立了颜色空间转换RBF网络模型,并通过增加样本数据,采用动态规划颜色子空间的方法,提高了模型转换精度。研究结果显示,该方法的转换速度和精度都优于基于动态子空间自动划分的BP神经网络颜色空间转换方法。更多还原

【Abstract】 Radial basis function(RBF) neural network was applied to study the conversion of color values between different color space by using the color space conversion of RGB to CIE L*a*b* as example.RBF neural network model of color space conversion was established by using basic data sets of sample.The precision of model conversion was improved by adding sample data and using color subspace dynamic planning method.The result showed that the conversion speed and precision of this method is better than dynamic subspace automatic divided BP neural network color space conversion method.更多还原