Multi-color balance for color constancy
Not on the map. Why?
Abstract (arXiv)
In this paper, we propose a novel multi-color balance adjustment for color constancy. The proposed method, called "n-color balancing," allows us not only to perfectly correct n target colors on the basis of corresponding ground truth colors but also to correct colors other than the n colors. In contrast, although white-balancing can perfectly adjust white, colors other than white are not considered in the framework of white-balancing in general. In an experiment, the proposed multi-color balancing is demonstrated to outperform both conventional white and multi-color balance adjustments including Bradford's model.
Key facts. Cited by 3 papers in the map (data through 13 Oct 2026). Builds on 6 of its 30 references that are in the map. First posted on arXiv 21 May 2021.
Builds on
6 of 30 references.
References · 6
- 2020Deep White-Balance Editingcited by 54
- 2019What Else Can Fool Deep Learning? Addressing Color Constancy Errors on Deep Neural Network Performancecited by 37
- 2019Scene Segmentation-Based Luminance Adjustment for Multi-Exposure Image Fusioncited by 15
- 2020Fast Soft Color Segmentationcited by 13
- 2018Rehabilitating the ColorChecker Dataset for Illuminant Estimationcited by 7
- 2021Multi-color balancing for correctly adjusting the intensity of target colorscited by 3
Built on by
Citing papers per year: 2021: 1; 2022: 1; 2023: 0; 2024: 1.
3 papers.