Efficient illuminant estimation for color constancy using grey pixels

Kai-Fu Yang, Shaobing Gao, Yongjie Li
{"title":"Efficient illuminant estimation for color constancy using grey pixels","authors":"Kai-Fu Yang, Shaobing Gao, Yongjie Li","doi":"10.1109/CVPR.2015.7298838","DOIUrl":null,"url":null,"abstract":"Illuminant estimation is a key step for computational color constancy. Instead of using the grey world or grey edge assumptions, we propose in this paper a novel method for illuminant estimation by using the information of grey pixels detected in a given color-biased image. The underlying hypothesis is that most of the natural images include some detectable pixels that are at least approximately grey, which can be reliably utilized for illuminant estimation. We first validate our assumption through comprehensive statistical evaluation on diverse collection of datasets and then put forward a novel grey pixel detection method based on the illuminant-invariant measure (IIM) in three logarithmic color channels. Then the light source color of a scene can be easily estimated from the detected grey pixels. Experimental results on four benchmark datasets (three recorded under single illuminant and one under multiple illuminants) show that the proposed method outperforms most of the state-of-the-art color constancy approaches with the inherent merit of low computational cost.","PeriodicalId":444472,"journal":{"name":"2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","volume":"427 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"115","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CVPR.2015.7298838","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 115

Abstract

Illuminant estimation is a key step for computational color constancy. Instead of using the grey world or grey edge assumptions, we propose in this paper a novel method for illuminant estimation by using the information of grey pixels detected in a given color-biased image. The underlying hypothesis is that most of the natural images include some detectable pixels that are at least approximately grey, which can be reliably utilized for illuminant estimation. We first validate our assumption through comprehensive statistical evaluation on diverse collection of datasets and then put forward a novel grey pixel detection method based on the illuminant-invariant measure (IIM) in three logarithmic color channels. Then the light source color of a scene can be easily estimated from the detected grey pixels. Experimental results on four benchmark datasets (three recorded under single illuminant and one under multiple illuminants) show that the proposed method outperforms most of the state-of-the-art color constancy approaches with the inherent merit of low computational cost.
基于灰度像素的彩色恒常性光源估计方法
光源估计是计算颜色常数的关键步骤。本文提出了一种利用给定色差图像中检测到的灰度像素信息来估计光源的新方法,而不是使用灰色世界或灰色边缘假设。潜在的假设是,大多数自然图像包括一些可检测的像素,至少是近似灰色的,这可以可靠地用于光源估计。首先通过对不同数据集的综合统计评估验证了我们的假设,然后提出了一种基于三对数颜色通道的光照不变测度(IIM)的灰度像素检测方法。这样就可以很容易地从检测到的灰度像素中估计出场景的光源颜色。在4个基准数据集(3个单光源数据集和1个多光源数据集)上的实验结果表明,该方法具有计算成本低的固有优点,优于大多数现有的颜色恒常性方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信