摘要
针对红外与可见光图像融合中边缘模糊、对比度较低的问题,提出一种二维窗口经验模式分解(WEMD)和生成对抗网络重建的红外与可见光图像融合算法。将红外和可见光图像进行WEMD分解得到内蕴模式函数分量和残余分量,将内蕴模式函数分量通过主成分分析进行融合,残余分量用加权平均进行融合,重构得到初步融合图像,再将初步融合图像输入生成对抗网络中与可见光图像进行对抗博弈,补全背景信息,得到最终的融合图像。客观评价指标采用平均梯度、边缘强度、熵值、结构相似性和互信息,与其他5种方法相比,本文算法的各项指标分别平均提高了46.13%,39.40%,19.91%,3.72%,33.10%。实验结果表明,该算法较好地保留了源图像的边缘及纹理细节信息,同时突出了红外图像的目标,具有较好的可视性,而且在客观评价指标方面也有明显的优势。
To overcome the problem of blurred edges and low contrast in the fusion of infrared and visible images,a two-dimensional window empirical mode decomposition(WEMD)and infrared and visible light image fusion algorithm for GAN reconstruction was proposed.The infrared and visible light images were decomposed using WEMD to obtain the intrinsic mode function components(IMF)and residual components.The IMF components were fused through principal component analysis,and the residual components were fused by the weighted average.The preliminary fused image was reconstructed and input into the GAN to play against the visible light image,and some background information was supplemented to obtain the final fusion image.The average gradient(AG),edge strength(EI),entropy(EN),structural similarity(SSIM),and mutual information(MI)are used for objective evaluation,and they increased by 46.13%,39.40%,19.91%,3.72%,and 33.10%,respectively,compared with the other five methods.The experimental results show that the proposed algorithm achieves better retention of the edge and texture details of the sources image while simultaneously highlighting the target of the infrared image,has better visibility,and has obvious advantages in terms of objective evaluation indicators.
作者
杨艳春
高晓宇
党建武
王阳萍
YANG Yanchun;GAO Xiaoyu;DANG Jianwu;WANG Yangping(School of Electronic and Information Engineering,Lanzhou Jiaotong University,Lanzhou 730070,China)
出处
《光学精密工程》
EI
CAS
CSCD
北大核心
2022年第3期320-330,共11页
Optics and Precision Engineering
基金
长江学者和创新团队发展计划资助项目(No.IRT_16R36)
国家自然科学基金资助项目(No.62067006)
甘肃省科技计划资助项目(No.18JR3RA104)
甘肃省高等学校产业支撑计划资助项目(No.2020C-19)
兰州市科技计划资助项目(No.2019-4-49)
兰州交通大学天佑创新团队资助项目(No.TY202003)
兰州交通大学-天津大学联合创新基金资助项目(No.2021052)。
关键词
图像融合
红外与可见光图像
窗口经验模式分解
生成对抗网络
image fusion
infrared and visible image
window empirical mode decomposition
generative adversarial network
