彩色扫描仪的特征化

徐艳芳; 刘文耀; 左坤隆; 朱昊

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彩色扫描仪的特征化

现代光学仪器与精密机械 | 更新时间：2020-08-12

- 彩色扫描仪的特征化
- Characterization of color scanners
- 光学精密工程 2004年12卷第1期页码：15-20
- 作者机构：
  
  天津大学, 精密仪器与光电子工程学院, 光电信息技术科学教育部重点实验室, 天津, 300072
- 作者简介：
- 基金信息：
- DOI：
  中图分类号： O432.3;TP334.8
- 收稿日期：2003-09-16，
  
  修回日期：2003-12-19，
  
  网络出版日期：2004-02-15，
  
  纸质出版日期：2004-02-15
- 稿件说明：
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徐艳芳, 刘文耀, 左坤隆, 朱昊. 彩色扫描仪的特征化[J]. 光学精密工程, 2004,(1): 15-20

XU Yan-fang, LIU Wen-yao, ZUO Kun-long, ZHU Hao. Characterization of color scanners[J]. Editorial Office of Optics and Precision Engineering, 2004,(1): 15-20
徐艳芳, 刘文耀, 左坤隆, 朱昊. 彩色扫描仪的特征化[J]. 光学精密工程, 2004,(1): 15-20 DOI：

XU Yan-fang, LIU Wen-yao, ZUO Kun-long, ZHU Hao. Characterization of color scanners[J]. Editorial Office of Optics and Precision Engineering, 2004,(1): 15-20 DOI：

摘要

阐述了扫描仪特征化的原理和方法.采用多项式回归和人工神经网络技术

建立了扫描仪记录的RGB信息和原影像CIEXYZ及CIELAB色度信息之间的非线性对应关系.对4个常用扫描仪

实验得到了合理的多项式和人工神经网络结构.发现多项式项数为10较为合适

达到的CIELAB平均色差和最大色差分别在1.6～3.0和8～13个色差单位之间;6个隐含层神经元为人工神经网络较为合理的结构

达到的CIELAB平均色差和最大色差分别在1.4～2.6和6～8个色差单位之间.实验结果表明

对常用扫描仪的特征化

可采用多项式回归或人工神经网络技术

其中人工神经网络技术精度较高.

Abstract

The nonlinear relationship between the scanner RGB signals and original image CIEXYZ or CIELAB values were obtained using the polynomial regression and the artificial neural network procedures. The reasonable structures of the polynomial and the artificial neural network were found for four color scanners. The better number of polynomial terms was 10

reaching the accuracy of 1.6～3.0 CDU(color difference unit)CIELAB average CD(color difference)and 8～13 CDU CIELAB maximal CD. And the reasonable number of hidden cells of the network was 6

reaching the accuracy of 1.4～2.6 CDU CIELAB average CD and 6～8 CDU CIELAB maximal CD. The test results showed that the polynomial regression and the artificial neural network techniques could be used to characterize commonly used color scanners

and the latter has a higher accuracy.

关键词

Keywords

references

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