Extending depth-of-field of a digital camera using particle swarm optimization based image fusion

V. Aslantaş, Rifat Kurban
{"title":"Extending depth-of-field of a digital camera using particle swarm optimization based image fusion","authors":"V. Aslantaş, Rifat Kurban","doi":"10.1109/ISCE.2010.5523731","DOIUrl":null,"url":null,"abstract":"Images obtained by an optical camera are seriously affected from the limited depth of the field issue. That is, the objects located in-front-of or behind the focus of the camera are blurred. Everywhere-in-focus images can be obtained by combining focused regions of images which were captured by different focal settings. In this paper, an optimal region based spatial domain image fusion approach based on selecting sharper regions from the multi-focus source images is proposed. Size of the block type regions are optimized by using particle swarm optimization (PSO) algorithm. Quantitative and subjective experimental results of different image sets show that proposed method is better than traditional wavelet and Laplacian pyramid based and also genetic algorithm (GA) based methods.","PeriodicalId":403652,"journal":{"name":"IEEE International Symposium on Consumer Electronics (ISCE 2010)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE International Symposium on Consumer Electronics (ISCE 2010)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCE.2010.5523731","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

Images obtained by an optical camera are seriously affected from the limited depth of the field issue. That is, the objects located in-front-of or behind the focus of the camera are blurred. Everywhere-in-focus images can be obtained by combining focused regions of images which were captured by different focal settings. In this paper, an optimal region based spatial domain image fusion approach based on selecting sharper regions from the multi-focus source images is proposed. Size of the block type regions are optimized by using particle swarm optimization (PSO) algorithm. Quantitative and subjective experimental results of different image sets show that proposed method is better than traditional wavelet and Laplacian pyramid based and also genetic algorithm (GA) based methods.
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
基于粒子群算法的图像融合扩展数码相机的景深
由于景深有限的问题,严重影响了光学相机的成像效果。也就是说,位于相机焦点前后的物体是模糊的。将不同对焦设置所捕获的图像的聚焦区域进行组合,即可获得全焦图像。本文提出了一种基于区域的空间域图像融合方法,该方法基于从多聚焦源图像中选择更清晰的区域。采用粒子群算法对块型区域的大小进行优化。不同图像集的定量和主观实验结果表明,该方法优于传统的基于小波变换和拉普拉斯金字塔的方法以及基于遗传算法(GA)的方法。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
An 80 mW dual video-codec SoC for seamless playback of digital terrestrial television and mobile broadcasting services Scalable high quality nonlinear up-scaler with guaranteed real time performance Optimized temporal scalability for H.264 based codecs and its applications to video conferencing Human body communication system with FSBT Synchronizing multimodal user input information in a modular mobile software platform
×
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