Abstract
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.
Highlights
A change in illumination affects the pixel values of an image taken with an RGB digital camera because the values are determined by spectral information such as the spectra of illumination [1,2,3]
The proposed method was applied to the input images, and it was compared with white balancing and Cheng’s method (Cheng (1–24)), where XYZ scaling (WB (XYZ)) and von Kries’s model (WB) were applied as white balance adjustments
Evaluation of Computational Complexity In Cheng’s method, all of the 24 patches in a color rendition chart are used as target colors
Summary
A change in illumination affects the pixel values of an image taken with an RGB digital camera because the values are determined by spectral information such as the spectra of illumination [1,2,3]. In the human visual system, it is well known that illumination changes (i.e., lighting effects) are reduced, and this ability keeps the entire color perception of a scene constant [4]. Since cameras do not intrinsically have this ability, white balancing is applied to images [5]. Applying white balancing requires a two-step procedure: estimating a white region with remaining lighting effects (i.e., a source white point) and mapping the estimated white region into the ground truth white without lighting effects. Many studies have focused on estimating a source white point in images [11,12,13,14,15,16,17,18,19].
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