A fast multi-focus image fusion algorithm by DWT and focused region decision map

Shumin Liu, Jiajia Chen
{"title":"A fast multi-focus image fusion algorithm by DWT and focused region decision map","authors":"Shumin Liu, Jiajia Chen","doi":"10.1109/APSIPA.2016.7820864","DOIUrl":null,"url":null,"abstract":"To comprise the advantages of both the spatial domain and transform domain methods, this paper presents a novel hybrid algorithm for multi-focus images fusion, which reduces the error rate of sub-band coefficients selection in the transform domain and reduce the artificial discontinuities created in the spatial domain algorithms. In this method, wavelet transforms are firstly performed on each input image, and a focused region decision map is established based on the high-frequency sub-bands extraction. The fusion rules are then guided by this map, and the fused coefficients are transformed back to form the fused image. Experimental results demonstrate that the proposed method is better than various existing methods, in term of fusion quality benchmarks. In addition, the proposed algorithm has a complexity proportional to the total number of pixels in the image, which is lower than some other algorithm which may produce similar fusion quality with the proposed algorithm. Furthermore, the proposed algorithm only requires one level wavelet decomposition, again reducing the processing time. With the proposed method, high quality and fast multi-focus image fusion is made possible.","PeriodicalId":409448,"journal":{"name":"2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)","volume":"107 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APSIPA.2016.7820864","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13

Abstract

To comprise the advantages of both the spatial domain and transform domain methods, this paper presents a novel hybrid algorithm for multi-focus images fusion, which reduces the error rate of sub-band coefficients selection in the transform domain and reduce the artificial discontinuities created in the spatial domain algorithms. In this method, wavelet transforms are firstly performed on each input image, and a focused region decision map is established based on the high-frequency sub-bands extraction. The fusion rules are then guided by this map, and the fused coefficients are transformed back to form the fused image. Experimental results demonstrate that the proposed method is better than various existing methods, in term of fusion quality benchmarks. In addition, the proposed algorithm has a complexity proportional to the total number of pixels in the image, which is lower than some other algorithm which may produce similar fusion quality with the proposed algorithm. Furthermore, the proposed algorithm only requires one level wavelet decomposition, again reducing the processing time. With the proposed method, high quality and fast multi-focus image fusion is made possible.
一种基于小波变换和聚焦区域决策图的快速多焦点图像融合算法
结合空间域和变换域方法的优点,提出了一种新的多焦点图像融合混合算法,降低了变换域子带系数选择的错误率,减少了空间域算法中产生的人为不连续。该方法首先对输入图像进行小波变换,并在提取高频子带的基础上建立焦点区域决策图。然后利用该映射来指导融合规则,并将融合系数变换回来形成融合图像。实验结果表明,该方法在融合质量基准方面优于现有的各种方法。此外,本文算法的复杂度与图像中像素的总数成正比,比其他可能产生与本文算法相似的融合质量的算法要低。此外,该算法只需要一级小波分解,再次减少了处理时间。该方法可实现高质量、快速的多焦点图像融合。
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