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作 者:付晓凡 徐杨[1] 李长军 Fu Xiaofan;Xu Yang;Li Changjun(College of Computer and Software Engineering,University of Science and Technology,Anshan,Liaoning 114051,China)
机构地区:[1]辽宁科技大学计算机与软件工程学院,辽宁鞍山114051
出 处:《激光与光电子学进展》2021年第14期499-505,共7页Laser & Optoelectronics Progress
基 金:国家自然科学基金(61575090,61775169);辽宁省教育厅项目(2017LNQN07)。
摘 要:研究了相机JPG数据线性化对基于加权多项式回归算法的光谱反射重建精度的影响,论证了是否需要在加权多项式回归算法中对JPG数据进行线性化处理。实验采用加权多项式回归算法重建反射率,以X-Rite Digital ColorChecker Semi Gloss(SG)色卡(包括140个色块和灰色色块)进行训练,GretagMacbeth ColorChecker色卡(包括24个色块和灰色色块)和自制的44个印刷样品及48个纺织品样品做测试。采用CIEDE2000色差和均方根误差将结果与真实数据进行对比,结果表明,在加权多项式回归算法中使用原始JPG数据的效果要优于使用线性化JPG数据。基于该研究结果,对JPG数据进行线性化处理并不能提高加权多项式回归算法重建反射率的重建精度。而不进行JPG数据线性化,同样可以得到较高的光谱重建精度。在三阶加权多项式回归算法中,使用原始JPG数据的重建效果最好。This paper investigates the effect of the linearization of camera JPG data on the accuracy of spectral reflectance reconstruction based on weighted polynomial regression algorithm and demonstrates whether the JPG data needs to be linearized in the weighted polynomial regression algorithm.This method was trained using the XRite Digital ColorChecker Semi Gloss(SG)chart including 140 color and grey patches and tested using the GretagMacbeth ColorChecker chart including 24 color and grey patches,and self-made 44 printed and 48 textile samples.Comparison results based on real camera data have shown that the weighted polynomial regression method with the original JPG data outperformed the weighted polynomial regression method with the linearized JPG data measured in terms of CIEDE2000 color difference and root-mean-square error.Based on the results of this study,linearization of the JPG data does not improve the reconstruction accuracy for reconstructing the reflectance using the weighted polynomial regression method.Without JPG data linearization,higher spectral reconstruction accuracy can also be obtained.The weighted three order polynomial regression method performed the best with original JPG data.
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