Tominaga S, Ebisui S, Wandell B A
Department of Engineering Informatics, Osaka Electro-Communication University, Neyagawa, Japan.
J Opt Soc Am A Opt Image Sci Vis. 2001 Jan;18(1):55-64. doi: 10.1364/josaa.18.000055.
Knowledge of the scene illuminant spectral power distribution is useful for many imaging applications, such as color image reproduction and automatic algorithms for image database applications. In many applications accurate spectral characterization of the illuminant is impossible because the input device acquires only three spectral samples. In such applications it is sensible to set a more limited objective of classifying the illuminant as belonging to one of several likely types. We describe a data set of natural images with measured illuminants for testing illuminant classification algorithms. One simple type of algorithm is described and evaluated by using the new data set. The empirical measurements show that illuminant information is more reliable in bright regions than in dark regions. Theoretical predictions of the algorithm's classification performance with respect to scene illuminant blackbody color temperature are tested and confirmed by using the natural-image data set.
了解场景光源的光谱功率分布对许多成像应用很有用，比如彩色图像再现以及图像数据库应用中的自动算法。在许多应用中，由于输入设备仅获取三个光谱样本，因此无法准确表征光源的光谱。在这类应用中，将光源分类为几种可能类型之一的目标更为合理。我们描述了一个带有测量光源的自然图像数据集，用于测试光源分类算法。通过使用新数据集描述并评估了一种简单的算法类型。实验测量表明，光源信息在明亮区域比在黑暗区域更可靠。利用自然图像数据集对算法关于场景光源黑体色温的分类性能进行了理论预测并得到证实。
