Optical flow estimation technique for hazy scenes

Rao Kashif, Sana Rao
{"title":"Optical flow estimation technique for hazy scenes","authors":"Rao Kashif, Sana Rao","doi":"10.1109/icodt255437.2022.9805761","DOIUrl":null,"url":null,"abstract":"Hazy scenes limit the visibility and make the optical flow estimation task challenging due to low contrast images. Previous methods are not robust when applied to hazy image sequences because the two assumptions (brightness constancy and smoothness) break down due to the low contrast outdoor effects. Based on the pre-processing work on images, we applied an image dehazing method on image sequences first to handle haze and then estimated optical flow. The proposed method is based on a classical pyramidal technique. Results show that our method performs well on hazy scenes as compared to the other existing method.","PeriodicalId":291030,"journal":{"name":"2022 2nd International Conference on Digital Futures and Transformative Technologies (ICoDT2)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 2nd International Conference on Digital Futures and Transformative Technologies (ICoDT2)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/icodt255437.2022.9805761","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Hazy scenes limit the visibility and make the optical flow estimation task challenging due to low contrast images. Previous methods are not robust when applied to hazy image sequences because the two assumptions (brightness constancy and smoothness) break down due to the low contrast outdoor effects. Based on the pre-processing work on images, we applied an image dehazing method on image sequences first to handle haze and then estimated optical flow. The proposed method is based on a classical pyramidal technique. Results show that our method performs well on hazy scenes as compared to the other existing method.
朦胧场景光流估计技术
朦胧场景限制了能见度,并且由于图像对比度低,使得光流估计任务具有挑战性。以往的方法在模糊图像序列上的鲁棒性较差,因为低对比度的室外效果会破坏两个假设(亮度恒定和平滑)。在对图像进行预处理的基础上,首先对图像序列进行图像去雾处理,然后估计光流。提出的方法是基于经典的金字塔技术。结果表明,与现有的方法相比,该方法在雾蒙蒙的场景下表现良好。
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:481959085
Book学术官方微信