An Infrared and Visible Image Fusion Method Guided by Saliency and Gradient Information
Q. Li; G. Han; P. Liu; H. Yang; J. Wu and D. Liu
刊名IEEE Access
2021
卷号9页码:108942-108958
ISSN号21693536
DOI10.1109/ACCESS.2021.3101639
英文摘要Infrared and visible image fusion is a hot topic due to the perfect complementarity of their information. There are two key problems in infrared and visible image fusion. One is how to extract significant target areas and rich texture details from the source images, and the other is how to integrate them to produce satisfactory fused images. To tackle these problems, we propose a novel fusion framework in this paper. A multi-level image decomposition method is used to obtain the base layer and detail layer of the source image. For the fusion of base layer, an ingenious fusion strategy guided by the saliency map of source image is designed to improve the intensity of salient targets and the visual quality of the fused image. For the fusion of detail layer, an efficient approach by introducing the enhanced gradient information is presented to boost the detail features and sharpen the edges of the fused image. Experimental results demonstrate that, compared with fifteen classical and advanced fusion methods, the proposed image fusion framework has better performance in both subjective and objective evaluation. 2013 IEEE.
URL标识查看原文
内容类型期刊论文
源URL[http://ir.ciomp.ac.cn/handle/181722/65344]  
专题中国科学院长春光学精密机械与物理研究所
推荐引用方式
GB/T 7714
Q. Li,G. Han,P. Liu,et al. An Infrared and Visible Image Fusion Method Guided by Saliency and Gradient Information[J]. IEEE Access,2021,9:108942-108958.
APA Q. Li,G. Han,P. Liu,H. Yang,&J. Wu and D. Liu.(2021).An Infrared and Visible Image Fusion Method Guided by Saliency and Gradient Information.IEEE Access,9,108942-108958.
MLA Q. Li,et al."An Infrared and Visible Image Fusion Method Guided by Saliency and Gradient Information".IEEE Access 9(2021):108942-108958.
个性服务
查看访问统计
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。


©版权所有 ©2017 CSpace - Powered by CSpace