Niu Shijun, Wu Guangyuan, Li Xiaozhou
Faculty of Light Industry, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China.
State Key Laboratory of Biobased Material and Green Papermaking, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China.
Sensors (Basel). 2023 May 31;23(11):5225. doi: 10.3390/s23115225.
Spectral filters are an important part of a multispectral acquisition system, and the selection of suitable filters can improve the spectral recovery accuracy. In this paper, we propose an efficient human color vision-based method to recover spectral reflectance by the optimal filter selection. The original sensitivity curves of the filters are weighted using the LMS cone response function. The area enclosed by the weighted filter spectral sensitivity curves and the coordinate axis is calculated. The area is subtracted before weighting, and the three filters with the smallest reduction in the weighted area are used as the initial filters. The initial filters selected in this way are closest to the sensitivity function of the human visual system. After the three initial filters are combined with the remaining filters one by one, the filter sets are substituted into the spectral recovery model. The best filter sets under L-weighting, M-weighting, and S-weighting are selected according to the custom error score ranking. Finally, the optimal filter set is selected from the three optimal filter sets according to the custom error score ranking. The experimental results demonstrate that the proposed method outperforms existing methods in spectral and colorimetric accuracy, which also has good stability and robustness. This work will be useful for optimizing the spectral sensitivity of a multispectral acquisition system.
光谱滤光片是多光谱采集系统的重要组成部分，选择合适的滤光片可以提高光谱恢复精度。在本文中，我们提出了一种基于人类颜色视觉的有效方法，通过最优滤光片选择来恢复光谱反射率。利用LMS视锥细胞响应函数对滤光片的原始灵敏度曲线进行加权。计算加权后的滤光片光谱灵敏度曲线与坐标轴所围成的面积。在加权前减去该面积，并将加权面积减小最小的三个滤光片用作初始滤光片。以这种方式选择的初始滤光片最接近人类视觉系统的灵敏度函数。将三个初始滤光片与其余滤光片逐一组合后，将滤光片组代入光谱恢复模型。根据自定义误差得分排名，选择L加权、M加权和S加权下的最佳滤光片组。最后，根据自定义误差得分排名从三个最优滤光片组中选择最优滤光片组。实验结果表明，所提方法在光谱和色度精度方面优于现有方法，且具有良好的稳定性和鲁棒性。这项工作将有助于优化多光谱采集系统的光谱灵敏度。
