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Spectral Image Color Separation Algorithm Based on Cellular Yule-Nielson Spectral Neugebauer Model

机译:基于细胞Yule-Nielson光谱Neugebauer模型的光谱图像分色算法

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摘要

Spectral Neugebauer has become a focus because the model has specific physical meaning among all the spectral characteristic model of output devices. In order to improve the precision of the model, Spectral Neugebauer was modified by cell-element and Yule-Nielson exponent, which is called the Cellular Yule-Nielson Spectral Neugebauer (abbreviated as CYNSN). Although CYNSN forward model accuracy is high, but the precision and the efficiency of reverse model (that is, spectral image color separation model) is low. Arming to CYNSN reverse model (spectral image color separation), an adaptive CYNSN reverse model was proposed in this article. Compared with the existing model, the experimental results show that the proposed adaptive spectral color separation model has the same accuracy with the existing model, but efficiency has a great improvement, can achieve about 12.83 times as many of the existing model.
机译:光谱Neugebauer成为焦点,因为该模型在输出设备的所有光谱特征模型中具有特定的物理意义。为了提高模型的精度,通过单元元素和Yule-Nielson指数对光谱Neugebauer进行了修改,称为细胞Yule-Nielson光谱Neugebauer(缩写为CYNSN)。尽管CYNSN正向模型精度较高,但反向模型(即光谱图像分色模型)的精度和效率较低。针对CYNSN逆模型(光谱图像分色),本文提出了一种自适应CYNSN逆模型。与现有模型相比,实验结果表明,所提出的自适应光谱分色模型与现有模型具有相同的精度,但是效率有很大的提高,可以达到现有模型的约12.83倍。

著录项

  • 来源
  • 会议地点 Beijing(CN)
  • 作者单位

    Department of Printing and Packaging Engineering, Henan University of Animal Husbandry and Economy, Zhengzhou, Henan, China;

    Department of Printing and Packaging Engineering, Shanghai Publishing and Printing College, Shanghai, China;

    Department of Materials and Chemical Engineering, Henan Institute of Engineering, Zhengzhou, Henan, China;

    College of Communication and Art Design, University of Shanghai for Science and Technology, Shanghai, China;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Spectral image separation; CYNSN; Adaptive; Reverse model;

    机译:光谱图像分离; CYNSN;自适应逆向模型;

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