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基于孟塞尔系统的阴极射线管特性化新方法
引用本文:杨卫平,廖宁放,黄庆梅,郝建明,蒋绍全.基于孟塞尔系统的阴极射线管特性化新方法[J].光学学报,2004,24(8):039-1044.
作者姓名:杨卫平  廖宁放  黄庆梅  郝建明  蒋绍全
作者单位:北京理工大学信息科学技术学院颜色科学与工程国家专业实验室,北京,100081;云南师范大学物理与电子信息学院,昆明,650092;北京理工大学信息科学技术学院颜色科学与工程国家专业实验室,北京,100081;云南师范大学物理与电子信息学院,昆明,650092
基金项目:国家自然科学基金 (6 0 2 780 2 2 ),云南省自然科学基金(2 0 0 0A0 0 4 4M)资助课题
摘    要:提出了一种新的阴极射线管特性化的方法。该方法的特点是采用“视觉匹配”方法,在反射体表面色和白发光体之间映射一些色貌因素,但没有使用任何复杂的色貌模型。是一种考虑了一些色貌因素的阴极射线管特性化方法。由于该问题的个性因素较多,采用BP神经网络实现色空间的非线性映射。实验结果表明,只要阴极射线管被标定,在办公室环境下,该方法可以改进在不同的阴极射线管上重现的颜色。采用3-7-7-3简单的网络结构;分色相样本训练。训练样本平均色差可以达到3.07L^*u^*v^*色差单位,测试样本平均色差可以达到4.55L^*u^*v^*色差单位,小于阴极射线管的最大可接受色差,结果是令人满意的。这在电子商务和办公自动化方面有广泛的用途。

关 键 词:色度学  色貌模型  颜色复制  阴极射线管特性化  神经网络
收稿时间:2003/6/23

A New Method of Cathode-Ray Tube Characterisation Based on Munsell System
Yang Weiping , Liao Ningfang Huang Qingmei Hao Jianmi ng Jiang Shaoquan National Laboratory of Color Science and Engineering,School of Information Science and Technology,Beijing Institute of Technology,Beijing School of Physics and Electron Information,Yunnan Normal University,Kunming.A New Method of Cathode-Ray Tube Characterisation Based on Munsell System[J].Acta Optica Sinica,2004,24(8):039-1044.
Authors:Yang Weiping  Liao Ningfang Huang Qingmei Hao Jianmi ng Jiang Shaoquan National Laboratory of Color Science and Engineering  School of Information Science and Technology  Beijing Institute of Technology  Beijing School of Physics and Electron Information  Yunnan Normal University  Kunming
Institution:Yang Weiping 1,2 Liao Ningfang1 Huang Qingmei1 Hao Jianmi ng2 Jiang Shaoquan2 1 National Laboratory of Color Science and Engineering,School of Information Science and Technology,Beijing Institute of Technology,Beijing 100081 2 School of Physics and Electron Information,Yunnan Normal University,Kunming 650092
Abstract:A new method of cathode-ray tube (CRT) monito rs characterization is proposed. The features of this method are, it adopted a vision matching method to map some color appearance factors between self-luminous body and reflector surface colors, but without the complexity of using any color appearance model. It is a method that it has considered some color appearance factors. The neural networks were utilized to realize nonlinear mapping in color space. The experiment indicated that the method may improve the reproduction colors in different CRT when an arbitrary assigned color is to be displayed on a CRT screen, in office environment. Some simple network structure and small samples training method were adopted. The average color difference of training samples is 3.07 L*u*v* unit and that of testing samples is 4.55 L*u*v*. These results are smaller than the biggest acceptable color difference 10 L*u*v* unit. The results are satisfying. The method can be widely used by electronic-commerce and automation in office.
Keywords:chromatics  color appearance model  color reproducti on  cathode-ray tube (CRT) characterization  neural network
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