一种区分图像雾霾与非雾霾的分类算法

Xiaoliang Yu, Chuangbai Xiao, M. Deng, Li Peng
{"title":"一种区分图像雾霾与非雾霾的分类算法","authors":"Xiaoliang Yu, Chuangbai Xiao, M. Deng, Li Peng","doi":"10.1109/ICIG.2011.22","DOIUrl":null,"url":null,"abstract":"The technology of image dehazing can only work for haze images, but in batch and real-time processing, only relying on human visual system judge whether the image is haze or non-haze image, is unrealistic, so how to determine whether there are haze or non-haze images is needed to be solved. In this paper, we proposed a method to judge whether a given image is haze. According to the difference between the haze and non-haze images, we extract three eigen values, including image visibility, intensity of dark channel and image contrast, then combine with support vector machine to make judgment of image state which is haze or non-haze, obtaining high recognition rate. Experimental results show that our method is feasible and effective. Our method for bath and real-time processing provide the basis for judging image state, promoting the wide application of image dehazing.","PeriodicalId":277974,"journal":{"name":"2011 Sixth International Conference on Image and Graphics","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"32","resultStr":"{\"title\":\"A Classification Algorithm to Distinguish Image as Haze or Non-haze\",\"authors\":\"Xiaoliang Yu, Chuangbai Xiao, M. Deng, Li Peng\",\"doi\":\"10.1109/ICIG.2011.22\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The technology of image dehazing can only work for haze images, but in batch and real-time processing, only relying on human visual system judge whether the image is haze or non-haze image, is unrealistic, so how to determine whether there are haze or non-haze images is needed to be solved. In this paper, we proposed a method to judge whether a given image is haze. According to the difference between the haze and non-haze images, we extract three eigen values, including image visibility, intensity of dark channel and image contrast, then combine with support vector machine to make judgment of image state which is haze or non-haze, obtaining high recognition rate. Experimental results show that our method is feasible and effective. Our method for bath and real-time processing provide the basis for judging image state, promoting the wide application of image dehazing.\",\"PeriodicalId\":277974,\"journal\":{\"name\":\"2011 Sixth International Conference on Image and Graphics\",\"volume\":\"46 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-08-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"32\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 Sixth International Conference on Image and Graphics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIG.2011.22\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 Sixth International Conference on Image and Graphics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIG.2011.22","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 32

摘要

图像去雾技术只能对雾霾图像起作用,但在批量和实时处理中,仅仅依靠人类视觉系统判断图像是雾霾图像还是非雾霾图像,是不现实的,因此如何判断是否存在雾霾或非雾霾图像是需要解决的。本文提出了一种判断给定图像是否为雾霾的方法。根据雾霾图像与非雾霾图像的差异,提取图像可见度、暗通道强度和图像对比度三个特征值,结合支持向量机对图像状态进行雾霾或非雾霾的判断,获得了较高的识别率。实验结果表明,该方法是可行和有效的。该方法为图像状态的判断提供了依据,促进了图像去雾技术的广泛应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Classification Algorithm to Distinguish Image as Haze or Non-haze
The technology of image dehazing can only work for haze images, but in batch and real-time processing, only relying on human visual system judge whether the image is haze or non-haze image, is unrealistic, so how to determine whether there are haze or non-haze images is needed to be solved. In this paper, we proposed a method to judge whether a given image is haze. According to the difference between the haze and non-haze images, we extract three eigen values, including image visibility, intensity of dark channel and image contrast, then combine with support vector machine to make judgment of image state which is haze or non-haze, obtaining high recognition rate. Experimental results show that our method is feasible and effective. Our method for bath and real-time processing provide the basis for judging image state, promoting the wide application of image dehazing.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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:481959085
Book学术官方微信