电子测量与仪器学报

冯贺,李立,赵凯.基于拉普拉斯分解耦合亮度调节的可见光与红外图像融合算法[J].电子测量与仪器学报,2020,34(10):142-148

基于拉普拉斯分解耦合亮度调节的可见光与红外图像融合算法

Fusion algorithm of visible and infrared image based on Laplace decomposition coupled with brightness adjustment

DOI：

英文关键词:visible and infrared image fusion Laplace decomposition brightness adjustment spatial frequency mean value feature

基金项目:国家自然科学基金河南省人才培养联合基金(U1204613)、河南省高等学校重点科研项目( 16A520034)、河南省科技攻关项目(172102310671)、河南省教育厅科学技术研究重点项目(15A510017)、河南省科技计划重点科技攻关项目(142102310188)资助

作者	单位
冯贺	1. 安阳工学院计算机科学与信息工程学院
李立	2. 安阳工学院电子信息与电气工程学院
赵凯	1. 安阳工学院计算机科学与信息工程学院，3. 中国石油大学(华东) 控制科学与工程学院

Author	Institution
Feng He	1. College of Computer Science and Engineering,Anyang University of Technology
Li Li	2. College of Electronic Information and Electrical Engineering, Anyang University of Technology
Zhao Kai	1. College of Computer Science and Engineering,Anyang University of Technology，3. School of Control Science and Engineering, China University of Petroleum (Hua Dong)

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中文摘要:

为了解决当前较多可见光与红外图像融合方法的融合结果中的目标信息不突出等问题,引入拉普拉斯分解机制,采用图像的亮度特征来融合可见光与红外图像。借助拉普拉斯分解方法,对输入图像进行分层,求取不同的图层信息。并利用图像的均值特征,计算图像的亮度信息,对低频图层的融合权值进行自适应调整,从而得到一个目标信息完整度较高的融合低频图层。基于图像的空间频率特征,对高频图层所含的细节丰富度进行评估,以获取一个细节丰富的融合高频图层。再利用拉普拉斯逆分解方法,对低、高频图层完成融合。实验数据显示,较已有的融合算法而言,所提算法的融合结果更能突出目标信息,具备更为丰富的细节特征。

英文摘要:

In order to solve the problem as the target information is not prominent in the fusion results of many visible and infrared image fusion methods. The Laplace decomposition mechanism is introduced to fuse the visible and infrared images with the brightness characteristics of the image. With the help of Laplace decomposition method, the input image is layered to obtain different layer information. Using the mean value of the image, the brightness information of the image is calculated, and the fusion weight of the lowfrequency layer is adjusted adaptively to obtain a low-frequency layer with high integrity of the target information. Based on the spatial frequency characteristics of the image, the detail richness of the high frequency layer is evaluated to obtain a fusion high frequency layer with rich details. And the low and high frequency layers are fused by using the Laplace inverse decomposition method. Experimental data show that the fusion results of the proposed algorithm can highlight the target information and have more detailed features than the existing fusion algorithms.

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