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Noise robustness of a colorimetric evaluation model for image acquisition devices with different characterization models

机译:具有不同特征模型的图像采集设备的比色评估模型的噪声鲁棒性

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摘要

Colorimetric evaluation of an image acquisition device is important for evaluating and optimizing a set of sensors. We have already proposed a colorimetric evaluation model [J. Imaging Sci. Technol. 49, 588-593 (2005)] based on the Wiener estimation. The mean square errors (MSE) between the estimated and the actual fundamental vectors by the Wiener filter and the proposed colorimetric quality (Qc) agree quite well with the proposed model and we have shown that the estimation of the system noise variance of the image acquisition system is essential for the evaluation model. In this paper, it is confirmed that the proposed model can be applied to two different reflectance recovery models, and these models provide us an easy method for estimating the proposed colorimetric quality (Qc). The influence of the system noise originates from the sampling intervals of the spectral characteristics of the sensors, the illuminations and the reflectance and the quantization error on the evaluation model are studied and it is confirmed from the experimental results that the proposed model holds even in a noisy condition.
机译:图像采集设备的比色评估对于评估和优化一组传感器非常重要。我们已经提出了比色评估模型[J.影像科学技术。 49,588-593(2005)]。由维纳滤波器估计的和实际的基本向量之间的均方误差(MSE)与所提出的比色质量(Qc)与所提出的模型非常吻合,并且我们已经表明,图像采集的系统噪声方差的估计系统对于评估模型至关重要。在本文中,已确认所提出的模型可以应用于两个不同的反射率恢复模型,并且这些模型为我们提供了一种简便的方法来估计所提出的比色质量(Qc)。系统噪声的影响源于传感器光谱特性的采样间隔,研究了照明度,反射率和量化误差对评估模型的影响,并通过实验结果证实了所提出的模型即使在一定的条件下也能成立。嘈杂的条件。

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