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首页> 外文期刊>Journal of the Optical Society of America, A. Optics, image science, and vision >Maintaining accuracy of cellular Yule-Nielsen spectral Neugebauer models for different ink cartridges using principal component analysis
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Maintaining accuracy of cellular Yule-Nielsen spectral Neugebauer models for different ink cartridges using principal component analysis

机译:使用主成分分析维持不同墨盒的蜂窝式Yule-Nielsen光谱Neugebauer模型的准确性

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摘要

The replacement of used-up ink cartridges is unavoidable, but it makes the existing characterization model far from accurate, while recharacterization is labor intensive. In this study, we propose a new correction method for cellular Yule-Nielsen spectral Neugebauer (CYNSN) models based on principal component analysis (PCA). First, a small set of correction samples are predicted, printed using new ink cartridges, and then measured. Second, the link between the predicted and measured reflectance weights, generated by PCA, is determined. The experimental results show that the proposed method provides a significant and robust improvement, since not only the color change between original and new inks but also the systemic error of CYNSN modelsis taken into account in the method.
机译:不可避免地要更换用完的墨盒,但这会使现有的表征模型变得不准确,而重新表征则需要大量劳动。在这项研究中,我们提出了一种基于主成分分析(PCA)的细胞Yule-Nielsen光谱Neugebauer(CYNSN)模型的新校正方法。首先,预测少量校正样本,使用新墨盒进行打印,然后进行测量。其次,确定PCA生成的预测反射率权重和测量反射率权重之间的联系。实验结果表明,该方法不仅考虑了原油墨与新油墨之间的颜色变化,而且考虑了CYNSN模型的系统误差,因此具有显着而稳健的改进。

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