On Finding Gray Pixels

Yanlin Qian, Joni-Kristian Kamarainen, Jarno Nikkanen, Jiri Matas; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019, pp. 8062-8070

Abstract


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.

Related Material


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[bibtex]
@InProceedings{Qian_2019_CVPR,
author = {Qian, Yanlin and Kamarainen, Joni-Kristian and Nikkanen, Jarno and Matas, Jiri},
title = {On Finding Gray Pixels},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2019}
}