We propose a novel grayness index for finding gray pixels and demonstrate its effectiveness and efficiency in illumination estimation. The grayness index, GI in short, is derived using the Dichromatic Reflection Model and is learning-free. GI allows to estimate one or multiple illumination sources in color-biased images. On standard single-illumination and multiple-illumination estimation benchmarks, GI outperforms state-of-the-art statistical methods and many recent deep methods. GI is simple and fast, written in a few dozen lines of code, processing a 1080p image in ~0.4 seconds with a non-optimized Matlab code.
@article{arxiv.1901.03198,
title = {On Finding Gray Pixels},
author = {Yanlin Qian and Joni-Kristian Kämäräinen and Jarno Nikkanen and Jiri Matas},
journal= {arXiv preprint arXiv:1901.03198},
year = {2019}
}
Comments
appear in IEEE International Conference on Computer Vision and Pattern Recognition (CVPR) 2019. 9 pages, 7 figures. this article is an extension of arXiv:1803.08326