@inproceedings{f967cf551b104b00804ce1b5404f7b2c,
title = "On Finding Gray Pixels",
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.",
keywords = "Computational Photography, Low-level Vision, Statistical Learning",
author = "Y. Qian and J. K{\"a}m{\"a}r{\"a}inen and Jarno Nikkanen and Jiri Matas",
note = "EXT={"}Matas, Jiri{"}; IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR ; Conference date: 01-01-2000",
year = "2019",
month = jun,
doi = "10.1109/CVPR.2019.00825",
language = "English",
isbn = "978-1-7281-3294-5",
series = "IEEE/CVF Conference on Computer Vision and Pattern Recognition",
publisher = "IEEE",
pages = "8054--8062",
booktitle = "2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
address = "United States",
}