Alsam Ali, Lenz Reiner
Gjøvik University College, Gjøvik, Norway.
J Opt Soc Am A Opt Image Sci Vis. 2007 Jan;24(1):11-7. doi: 10.1364/josaa.24.000011.
Spectral calibration of digital cameras based on the spectral data of commercially available calibration charts is an ill-conditioned problem that has an infinite number of solutions. We introduce a method to estimate the sensor's spectral sensitivity function based on metamers. For a given patch on the calibration chart we construct numerical metamers by computing convex linear combinations of spectra from calibration chips with lower and higher sensor response values. The difference between the measured reflectance spectrum and the numerical metamer lies in the null space of the sensor. For each measured spectrum we use this procedure to compute a collection of color signals that lie in the null space of the sensor. For a collection of such spaces we compute the robust principal components, and we obtain an estimate of the sensor by computing the common null space spanned by these vectors. Our approach has a number of advantages over standard techniques: It is robust to outliers and is not dominated by larger response values, and it offers the ability to evaluate the goodness of the solution where it is possible to show that the solution is optimal, given the data, if the calculated range is one dimensional.
基于市售校准图的光谱数据对数码相机进行光谱校准是一个病态问题,有无数个解。我们介绍一种基于同色异谱色来估计传感器光谱灵敏度函数的方法。对于校准图上的给定色块,我们通过计算来自具有较低和较高传感器响应值的校准芯片光谱的凸线性组合来构建数值同色异谱色。测量反射光谱与数值同色异谱色之间的差异位于传感器的零空间中。对于每个测量光谱,我们使用此过程来计算位于传感器零空间中的一组颜色信号。对于这样一组空间,我们计算稳健主成分,并通过计算这些向量所跨越的公共零空间来获得传感器的估计值。我们的方法相对于标准技术有许多优点:它对异常值具有鲁棒性,不受较大响应值的主导,并且能够在计算范围为一维时,在给定数据的情况下评估解的优劣,此时可以证明该解是最优的。