Akazawa Teruaki, Kinoshita Yuma, Shiota Sayaka, Kiya Hitoshi
Department of Computer Science, Tokyo Metropolitan University, 6-6 Asahigaoka, Tokyo 191-0065, Japan.
J Imaging. 2021 Oct 6;7(10):207. doi: 10.3390/jimaging7100207.
This paper presents a three-color balance adjustment for color constancy correction. White balancing is a typical adjustment for color constancy in an image, but there are still lighting effects on colors other than white. Cheng et al. proposed multi-color balancing to improve the performance of white balancing by mapping multiple target colors into corresponding ground truth colors. However, there are still three problems that have not been discussed: choosing the number of target colors, selecting target colors, and minimizing error which causes computational complexity to increase. In this paper, we first discuss the number of target colors for multi-color balancing. From our observation, when the number of target colors is greater than or equal to three, the best performance of multi-color balancing in each number of target colors is almost the same regardless of the number of target colors, and it is superior to that of white balancing. Moreover, if the number of target colors is three, multi-color balancing can be performed without any error minimization. Accordingly, we propose three-color balancing. In addition, the combination of three target colors is discussed to achieve color constancy correction. In an experiment, the proposed method not only outperforms white balancing but also has almost the same performance as Cheng's method with 24 target colors.
本文提出了一种用于颜色恒常性校正的三色平衡调整方法。白平衡是图像中颜色恒常性的典型调整方法,但除白色外的其他颜色仍存在光照影响。Cheng等人提出了多色平衡方法,通过将多个目标颜色映射到相应的真实颜色来提高白平衡的性能。然而,仍有三个问题尚未讨论:选择目标颜色的数量、选择目标颜色以及最小化导致计算复杂度增加的误差。在本文中,我们首先讨论多色平衡中目标颜色的数量。据我们观察,当目标颜色的数量大于或等于三个时,无论目标颜色的数量如何,每种目标颜色数量下多色平衡的最佳性能几乎相同,并且优于白平衡。此外,如果目标颜色的数量为三个,则可以在不进行任何误差最小化的情况下执行多色平衡。因此,我们提出了三色平衡。此外,还讨论了三种目标颜色的组合以实现颜色恒常性校正。在一项实验中,所提出的方法不仅优于白平衡,而且与Cheng等人使用24种目标颜色的方法具有几乎相同的性能。