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Research on Spectral Reconstruction Accuracy of Color Reproduction Based on PAC

机译:基于PAC的色彩再现光谱重建精度研究

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The key of spectrum color reproduction is to study the spectral information of original images, and reconstruct the spectral curve of the target color. The accuracy of reconstructed spectra is influenced by many factors. In order to study the influence factors of reconstruction accuracy, two kinds of color cards Munsell Color Matt and Color Checker Classic were selected as the spectral reflectance data samples, two kinds of linear dimension reduction models of PCA were established and different number basis vectors were selected to separately reconstruct the spectrum. Then the influence of the different models and the basis vector numbers on the reconstruction accuracy was evaluated. The experimental results showed that the accuracy by model one was better than that of model two in RMSE GFC and color difference. In two kinds of color cards, when the number of basis vectors obtained by model one reached 6, the color difference was less than 1, the RMSE was less than 0.01; the GFC was up to 0.999. So the optimal scheme of reconstructing spectral images is to select spectral dimension reduction model one and 6 basis vectors.
机译:光谱颜色再现的关键是研究原始图像的光谱信息,并重建目标颜色的光谱曲线。重建光谱的准确性受到许多因素的影响。为了研究重建精度的影响因素,选择了两种颜色卡片彩色马特和彩色检查器经典作为光谱反射数据样本,建立了两种PCA的线性尺寸减少模型,选择了不同的数量基础载体单独重建频谱。然后,评估了不同模型的影响和基础向量号对重建准确度进行了评估。实验结果表明,模型中的精度优于模型中的模型,在RMSE GFC中的色彩差异。在两种颜色卡中,当通过模型达到6获得的基载体数量时,色差小于1,RMSE小于0.01; GFC高达0.999。因此,重建频谱图像的最佳方案是选择频谱尺寸减少模型一个和6个基向量。

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