Revisiting Gray Pixel for Statistical Illumination Estimation
Computer Vision and Pattern Recognition
2019-01-10 v4
Abstract
We present a statistical color constancy method that relies on novel gray pixel detection and mean shift clustering. The method, called Mean Shifted Grey Pixel -- MSGP, is based on the observation: true-gray pixels are aligned towards one single direction. Our solution is compact, easy to compute and requires no training. Experiments on two real-world benchmarks show that the proposed approach outperforms state-of-the-art methods in the camera-agnostic scenario. In the setting where the camera is known, MSGP outperforms all statistical methods.
Keywords
Cite
@article{arxiv.1803.08326,
title = {Revisiting Gray Pixel for Statistical Illumination Estimation},
author = {Yanlin Qian and Said Pertuz and Jarno Nikkanen and Joni-Kristian Kämäräinen and Jiri Matas},
journal= {arXiv preprint arXiv:1803.08326},
year = {2019}
}
Comments
updated and will appear in VISSAP 2019 (long paper)