基于GA-Elman神经网络的LCD比色表征研究

Hongtai Guo, Tong Li, Zixuan Li, Qi Zheng
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引用次数: 0

摘要

LCD显示器的比色表征减少了显示设备在复制过程中图像颜色信息的失真,从而能够在不同的显示设备之间准确传输相同的图像。本文提出了一种基于Elman神经网络并采用遗传算法优化的GA-Elman模型。利用GA-Elman神经网络建立了从RGB到CIEXYZ的色彩空间转换,并对模型精度进行了分析。大量实验结果表明,该模型的最大色差为2.0800,平均色差为0.7300,色差性能优异,能够满足LCD比色表征的精度要求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Colorimetric Characterization of LCD Based on GA-Elman Neural Network
Colorimetric characterization for LCD displays reduces the distortion of the image color information during copying by the display device, enabling accurate transmission of the same image across different display devices. In this paper, we present a GA-Elman model based on the Elman neural network and optimized using genetic algorithm (GA). The color space conversion from RGB to CIEXYZ is established using the GA-Elman neural network, and finally the model accuracy is analyzed. A large number of experimental results show that the maximum chromatic aberration of the model is 2.0800, the average chromatic aberration is 0.7300, and the chromatic aberration performance is excellent, which can meet the accuracy requirements of colorimetric characterization of LCD.
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