Finlayson Graham D, Zhu Yuteng
IEEE Trans Image Process. 2021;30:853-867. doi: 10.1109/TIP.2020.3038523. Epub 2020 Dec 4.
When we place a colored filter in front of a camera the effective camera response functions are equal to the given camera spectral sensitivities multiplied by the filter spectral transmittance. In this article, we solve for the filter which returns the modified sensitivities as close to being a linear transformation from the color matching functions of the human visual system as possible. When this linearity condition - sometimes called the Luther condition- is approximately met, the 'camera+filter' system can be used for accurate color measurement. Then, we reformulate our filter design optimisation for making the sensor responses as close to the CIEXYZ tristimulus values as possible given the knowledge of real measured surfaces and illuminants spectra data. This data-driven method in turn is extended to incorporate constraints on the filter (smoothness and bounded transmission). Also, because how the optimisation is initialised is shown to impact on the performance of the solved-for filters, a multi-initialisation optimisation is developed. Experiments demonstrate that, by taking pictures through our optimised color filters, we can make cameras significantly more colorimetric.
当我们在相机前放置一个彩色滤光片时，有效的相机响应函数等于给定的相机光谱灵敏度乘以滤光片光谱透过率。在本文中，我们求解的滤光片要使修改后的灵敏度尽可能接近人类视觉系统颜色匹配函数的线性变换。当这个线性条件（有时称为路德条件）近似满足时，“相机 + 滤光片”系统可用于精确的颜色测量。然后，在已知实际测量表面和光源光谱数据的情况下，我们重新制定滤光片设计优化方案，以使传感器响应尽可能接近CIEXYZ三刺激值。这种数据驱动的方法进而扩展到纳入对滤光片的约束（平滑度和有限透射率）。此外，由于优化的初始化方式会影响求解出的滤光片的性能，因此开发了一种多初始化优化方法。实验表明，通过使用我们优化的彩色滤光片拍照，可以使相机在比色方面有显著提升。
