mlsanityData to 14 Oct 2026

Spatially varying white balancing for mixed and non-uniform illuminants

arXiv 2109.01350 ↗First posted 3 Sep 2021cs.CVcited by 1

Not on the map. Why?

Abstract (arXiv)

In this paper, we propose a novel white balance adjustment, called "spatially varying white balancing," for single, mixed, and non-uniform illuminants. By using n diagonal matrices along with a weight, the proposed method can reduce lighting effects on all spatially varying colors in an image under such illumination conditions. In contrast, conventional white balance adjustments do not consider the correcting of all colors except under a single illuminant. Also, multi-color balance adjustments can map multiple colors into corresponding ground truth colors, although they may cause the rank deficiency problem to occur as a non-diagonal matrix is used, unlike white balancing. In an experiment, the effectiveness of the proposed method is shown under mixed and non-uniform illuminants, compared with conventional white and multi-color balancing. Moreover, under a single illuminant, the proposed method has almost the same performance as the conventional white balancing.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 6 of its 21 references that are in the map. First posted on arXiv 3 Sep 2021.

Builds on

6 of 21 references.

References · 6

  1. 2020Deep White-Balance Editingcited by 54
  2. 2019What Else Can Fool Deep Learning? Addressing Color Constancy Errors on Deep Neural Network Performancecited by 37
  3. 2019Scene Segmentation-Based Luminance Adjustment for Multi-Exposure Image Fusioncited by 15
  4. 2020Fast Soft Color Segmentationcited by 13
  5. 2021Multi-color balancing for correctly adjusting the intensity of target colorscited by 3
  6. 2021Multi-color balance for color constancycited by 3

Built on by

Cited by year

Citing papers per year: 2022: 1.

1 paper.