Image Stabilization Based on Fusing the Visual Information in Differently Exposed Images

M. Tico, Markku Vehviläinen
{"title":"Image Stabilization Based on Fusing the Visual Information in Differently Exposed Images","authors":"M. Tico, Markku Vehviläinen","doi":"10.1109/ICIP.2007.4378905","DOIUrl":null,"url":null,"abstract":"The objective of image stabilization is to prevent or remove the motion blur degradation from images. We introduce a new approach to image stabilization based on combining information available in two differently exposed images of the same scene. In addition to the image normally captured by the system, with an exposure time determined by the illumination conditions, a very shortly exposed image is also acquired. The difference between the exposure times of the two images determines differences in their degradations which are exploited in order to recover the original image of the scene. We formulate the problem as a maximum a posteriori (MAP) estimation based on the degradation models of the two observed images, as well as by imposing an edge-preserving image prior. The proposed method is demonstrated through a series of simulation experiments, and visual examples on natural images.","PeriodicalId":131177,"journal":{"name":"2007 IEEE International Conference on Image Processing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2007-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 IEEE International Conference on Image Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIP.2007.4378905","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 21

Abstract

The objective of image stabilization is to prevent or remove the motion blur degradation from images. We introduce a new approach to image stabilization based on combining information available in two differently exposed images of the same scene. In addition to the image normally captured by the system, with an exposure time determined by the illumination conditions, a very shortly exposed image is also acquired. The difference between the exposure times of the two images determines differences in their degradations which are exploited in order to recover the original image of the scene. We formulate the problem as a maximum a posteriori (MAP) estimation based on the degradation models of the two observed images, as well as by imposing an edge-preserving image prior. The proposed method is demonstrated through a series of simulation experiments, and visual examples on natural images.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于不同曝光图像视觉信息融合的图像稳定
图像稳定的目的是防止或消除图像的运动模糊退化。我们介绍了一种基于结合同一场景的两张不同曝光图像中可用信息的图像稳定新方法。除了通常由系统捕获的图像外,在由照明条件决定的曝光时间下,还可以获得非常短的曝光图像。两幅图像的曝光时间的差异决定了它们的退化程度的差异,这些差异被用来恢复场景的原始图像。我们将问题表述为基于两个观测图像的退化模型的最大后验(MAP)估计,以及通过施加边缘保持图像先验。通过一系列的仿真实验和自然图像的视觉实例验证了该方法的有效性。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Block-Based Gradient Domain High Dynamic Range Compression Design for Real-Time Applications Generation of Layered Depth Images from Multi-View Video Detection Strategies for Image Cube Trajectory Analysis An Efficient Compression Algorithm for Hyperspectral Images Based on Correlation Coefficients Adaptive Three Dimensional Wavelet Zerotree Coding Enabling Introduction of Stereoscopic (3D) Video: Formats and Compression Standards
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1