Multifocus Image Fusion via Region Reconstruction

Jiangyong Duan, Gaofeng Meng, Shiming Xiang, Chunhong Pan
{"title":"Multifocus Image Fusion via Region Reconstruction","authors":"Jiangyong Duan, Gaofeng Meng, Shiming Xiang, Chunhong Pan","doi":"10.1109/ACPR.2013.92","DOIUrl":null,"url":null,"abstract":"This paper presents a new method for multifocus image fusion. We formulate the problem as an optimization framework with three terms to model common visual artifacts. A reconstruction error term is used to remove the boundary seam artifacts, and an out-of-focus energy term is used to remove the ringing artifacts. Together with an additional smoothness term, these three terms define the objective function of our framework. The objective function is then minimized by an efficient greedy iteration algorithm. Our method produces high quality fusion results with few visual artifacts. Comparative results demonstrate the efficiency of our method.","PeriodicalId":365633,"journal":{"name":"2013 2nd IAPR Asian Conference on Pattern Recognition","volume":" 9","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 2nd IAPR Asian Conference on Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACPR.2013.92","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

This paper presents a new method for multifocus image fusion. We formulate the problem as an optimization framework with three terms to model common visual artifacts. A reconstruction error term is used to remove the boundary seam artifacts, and an out-of-focus energy term is used to remove the ringing artifacts. Together with an additional smoothness term, these three terms define the objective function of our framework. The objective function is then minimized by an efficient greedy iteration algorithm. Our method produces high quality fusion results with few visual artifacts. Comparative results demonstrate the efficiency of our method.
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
基于区域重建的多焦点图像融合
提出了一种新的多焦点图像融合方法。我们将问题表述为一个优化框架,其中包含三个术语来建模常见的视觉工件。用重建误差项去除边界缝伪影,用离焦能量项去除振铃伪影。加上一个额外的平滑项,这三个项定义了我们框架的目标函数。然后用一种高效的贪婪迭代算法最小化目标函数。我们的方法产生高质量的融合结果,几乎没有视觉伪影。对比结果证明了该方法的有效性。
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
Automatic Compensation of Radial Distortion by Minimizing Entropy of Histogram of Oriented Gradients A Robust and Efficient Minutia-Based Fingerprint Matching Algorithm Sclera Recognition - A Survey A Non-local Sparse Model for Intrinsic Images Classification Based on Boolean Algebra and Its Application to the Prediction of Recurrence of Liver Cancer
×
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