摘要
针对红外与可见光图像融合中出现细节信息丢失及边缘模糊的问题,提出一种在变换域中通过VGGNet19网络的红外与可见光图像融合方法。首先,为了使得源图像在分解过程中提取到精度更高的基础与细节信息,将源图像利用具有保边平滑功能的多尺度引导滤波器进行分解,分解为一个基础层与多个细节层;然后,采用具有保留主要能量信息特点的拉普拉斯能量对基础层进行融合得到基础融合图;其次,为了防止融合结果丢失一些细节边缘信息,采用VGGNet19网络对细节层进行特征提取,L1正则化、上采样以及最终的加权平均策略得到融合后的细节部分;最后,通过两种融合图的相加即可得最终的融合结果。实验结果表明,本文方法更好地提取了源图像中的边缘及细节信息,在主观评价以及客观评价指标中均取得了更好的效果。
To address the problems of loss of detailed information and blurred edges in the fusion of infrared and visible images, an infrared and visible image fusion method through the VGGNet19 network in the transform domain is proposed. Firstly, in order to extract more accurate basic and detailed data from the source images during the decomposition process, the source images are decomposed using a multi-scale guided filter with edge-preserving smoothing function into a base layer and multiple detailed layers. Then, the Laplacian energy with the characteristics of retaining the main energy information is used to fuse the basic layer to obtain the basic fusion map. Subsequently, to prevent the fusion result from losing some detailed edge information,the VGGNet19 network is used to extract the features of the detail layers, L1 regularization, upsampling and final weighted average, thus the fused detail. Finally, the final fusion is obtained by adding two fusion graphs.The experimental results show that the method proposed can better extract the edge and detailed information in the source images, and achieve better results in terms of both subjective and objective evaluation indicators.
作者
李永萍
杨艳春
党建武
王阳萍
LI Yongping;YANG Yanchun;DANG Jianwu;WANG Yangping(School of Electronic and Information Engineering,Lanzhou Jiaotong University,Lanzhou 730070,China)
出处
《红外技术》
CSCD
北大核心
2022年第12期1293-1300,共8页
Infrared Technology
基金
长江学者和创新团队发展计划资助(IRT_16R36)
国家自然科学基金(62067006)
甘肃省科技计划项目(18JR3RA104)
甘肃省高等学校产业支撑计划项目(2020C-19)
兰州市科技计划项目(2019-4-49)
甘肃省教育厅:青年博士基金项目2022QB-067
甘肃省自然科学基金(21JR7RA300)
兰州交通大学天佑创新团队(TY202003)
兰州交通大学-天津大学联合创新基金项目(2021052)。
作者简介
李永萍(1996-),女,硕士研究生,主要研究方向:图像融合。E-mail:2647336295@qq.com;通信作者:杨艳春(1979-),女,副教授,主要研究方向:图像融合与图像配准。E-mail:yangyanchun102@sina.com。
