Probabilistic Color Constancy
Computer Vision and Pattern Recognition
2020-12-24 v1 Image and Video Processing
Abstract
In this paper, we propose a novel unsupervised color constancy method, called Probabilistic Color Constancy (PCC). We define a framework for estimating the illumination of a scene by weighting the contribution of different image regions using a graph-based representation of the image. To estimate the weight of each (super-)pixel, we rely on two assumptions: (Super-)pixels with similar colors contribute similarly and darker (super-)pixels contribute less. The resulting system has one global optimum solution. The proposed method achieves competitive performance, compared to the state-of-the-art, on INTEL-TAU dataset.
Cite
@article{arxiv.2005.02730,
title = {Probabilistic Color Constancy},
author = {Firas Laakom and Jenni Raitoharju and Alexandros Iosifidis and Uygar Tuna and Jarno Nikkanen and Moncef Gabbouj},
journal= {arXiv preprint arXiv:2005.02730},
year = {2020}
}
Comments
5 pages, 1 figure