Auto White-Balance Correction for Mixed-Illuminant Scenes

被引:20
作者
Afifi, Mahmoud [1 ]
Brubaker, Marcus A. [1 ,2 ]
Brown, Michael S. [1 ,2 ]
机构
[1] York Univ, N York, ON, Canada
[2] Vector Inst, Toronto, ON, Canada
来源
2022 IEEE WINTER CONFERENCE ON APPLICATIONS OF COMPUTER VISION (WACV 2022) | 2022年
基金
加拿大自然科学与工程研究理事会;
关键词
COLOR CONSTANCY; ALGORITHM;
D O I
10.1109/WACV51458.2022.00101
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Auto white balance (AWB) is applied by camera hardware at capture time to remove the color cast caused by the scene illumination. The vast majority of white-balance algorithms assume a single light source illuminates the scene; however, real scenes often have mixed lighting conditions. This paper presents an effective AWB method to deal with such mixed-illuminant scenes. A unique departure from conventional AWB, our method does not require illuminant estimation, as is the case in traditional camera AWB modules. Instead, our method proposes to render the captured scene with a small set of predefined white-balance settings. Given this set of rendered images, our method learns to estimate weighting maps that are used to blend the rendered images to generate the final corrected image. Through extensive experiments, we show this proposed method produces promising results compared to other alternatives for single- and mixed-illuminant scene color correction.
引用
收藏
页码:934 / 943
页数:10
相关论文
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