CVMay 21, 2021

Multi-color balance for color constancy

arXiv:2105.10228v17 citations
Originality Incremental advance
AI Analysis

This addresses color accuracy issues in image processing for applications like photography and computer vision, but it appears incremental as it builds on existing color balance adjustments.

The paper tackles the problem of color constancy by proposing a multi-color balance adjustment method that corrects multiple target colors and other colors, outperforming conventional methods like white-balancing and Bradford's model in experiments.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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