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Study on conversion method of color space under a big color gamut

机译:大色域下色彩空间的转换方法研究

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摘要

Since the equipment in computer color quantification system has different color gamut and color feature,accurate control and transmission of color information in this system is particularly difficult,and therefore the color luminance meter is selected for marking the color quantification system.Munsell color system is selected to establish the mutual conversion between RGB and L*a*b* color model for camera.The training set includes 1550 samples and the testing set includes 52 samples,which certainly will lead to the redundant problem of the hidden-layer node number,so the two-hiddenlayer neural network is considered.The training program,testing program and foreseeable program is compiled respectively by Neural Network Toolbox in Matlab applications.The conversion relation under a big color gamut is expressed by four-layer BP network.Through training this network,the training error is 0.000748566,using the data of testing set to test this network and calculating the color difference between forecast value and true value,the maximum color difference is 5.6357 NBS,the minimum color difference is 0.5311 NBS,and the average color difference is 3.1744 NBS.The result shows that the network can express the color quantitatively,and it is not subjective and vague,the quantitative mensuration and control of color could be done.
机译:由于计算机色彩量化系统中的设备具有不同的色域和色彩特征,因此在该系统中准确地控制和传输色彩信息非常困难,因此选择了色彩亮度计来标记色彩量化系统。选择了孟塞尔色彩系统建立相机的RGB和L * a * b *颜色模型之间的相互转换。训练集包含1550个样本,测试集包含52个样本,这肯定会导致隐藏层节点数的冗余问题,因此神经网络工具箱在Matlab应用中分别编译了训练程序,测试程序和可预见程序。在大色域下的转换关系由四层BP网络表示。 ,训练误差为0.000748566,使用测试集的数据对该网络进行测试并计算色差押注预测值与真实值之间的最大色差为5.6357 NBS,最小色差为0.5311 NBS,平均色差为3.1744 NBS。结果表明该网络可以定量地表达颜色,并且不是主观的,模糊,可以完成颜色的定量测定和控制。

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