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Infrared and visible image fusion based on edge-preserving guided filter and infrared feature decomposition
Ren, Long1,2,3; Pan, Zhibin2; Cao, Jianzhong1; Zhang, Hui1,3; Wang, Hao1
作者部门飞行器光学成像与测量技术研究室
2021-09
发表期刊Signal Processing
ISSN01651684
卷号186
产权排序1
摘要

Infrared (IR) images can distinguish salient targets from their backgrounds based on the radiation difference in all-weather conditions. By contrast, visible (VIS) images can contain high-resolution texture and details information, which is more suitable for human observation. Therefore, it is quite necessary to combine both imaging advantages of these two kinds of images. Compared with the existing methods, we believe that scale decomposition based methods are the most active and efficient image fusion methods, which also have the best fusion effects. Inspired by the present scale decomposition methods, we propose a new feature decomposition method. Firstly, we propose an improved guided filter called edge-preserving guided filter (EPGF), which adopts the image gradient map for further improving the filtering effect. Subsequently, by using the EPGF, we decompose the IR and VIS images into three kinds of layers, including salient feature layers, luminance layers and detail layers. At the same time, we combine all the layers together to get an initial fusion result. Finally, we optimize the initial fusion image according to a new image fusion optimization model and ADMM, and the final fusion result will be obtained after several iterations. Compared with other scale decomposition methods, our proposed feature decomposition based method takes the IR salient targets, IR and VIS background illumination, as well as VIS details into consideration which is more in line with human visual observation, besides the computational efficiency is also superior. Experimental results indicate that this method has better subjective and objective evaluation results compared with other state-of-the-art methods. © 2021 Elsevier B.V.

关键词Image fusion Edge-preserving guided filter Feature decomposition ADMM image optimization
DOI10.1016/j.sigpro.2021.108108
收录类别SCI ; EI
语种英语
WOS记录号WOS:000652606600008
出版者Elsevier B.V.
EI入藏号20211610223004
引用统计
被引频次:17[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.opt.ac.cn/handle/181661/94693
专题飞行器光学成像与测量技术研究室
通讯作者Ren, Long
作者单位1.Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an; 710119, China;
2.Faculty of electronics and communications of Xi'an Jiaotong University, Xi'an; 710049, China;
3.University of Chinese Academy of Sciences, No.19(A) Yuquan Road, Shijingshan District, Beijing; 100049, China
推荐引用方式
GB/T 7714
Ren, Long,Pan, Zhibin,Cao, Jianzhong,et al. Infrared and visible image fusion based on edge-preserving guided filter and infrared feature decomposition[J]. Signal Processing,2021,186.
APA Ren, Long,Pan, Zhibin,Cao, Jianzhong,Zhang, Hui,&Wang, Hao.(2021).Infrared and visible image fusion based on edge-preserving guided filter and infrared feature decomposition.Signal Processing,186.
MLA Ren, Long,et al."Infrared and visible image fusion based on edge-preserving guided filter and infrared feature decomposition".Signal Processing 186(2021).
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