系统工程与电子技术

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基于双边与高斯滤波混合分解的图像融合方法

周志强1,汪渤1,李立广2,李笋1   

  1. 1. 北京理工大学自动化学院, 北京 100081; 2.空军驻华北地区军事代表室, 北京 100086
  • 出版日期:2016-01-12 发布日期:2010-01-03

Image fusion based on a hybrid decomposition via bilateral and Gaussian filters

ZHOU Zhi-qiang1, WANG Bo1, LI Li-guang2, LI Sun1   

  1. 1. School of Automation, Beijing Institute of Technology, Beijing 100081, China; 2. Air Force Military Representative Office in Huabei Area, Beijing 100086, China
  • Online:2016-01-12 Published:2010-01-03

摘要:

针对红外与可见光图像融合时,两种异质图像信息容易相互干扰,造成融合图像出现模糊、信息混乱和对比度降低等问题,提出了一种基于双边与高斯滤波混合分解的融合方法。首先采用双边和高斯滤波器对输入的红外与可见光图像进行混合信息分解,得到小尺度纹理细节、大尺度边缘和底层粗略尺度图像信息;其中的大尺度边缘信息包含红外图像的主要特征,依据该特征确定各分解子信息的融合权重,从而将重要的红外特征信息注入到可见光图像;最后通过对各融合子信息进行组合重构出融合图像。实验结果表明,该算法融合效果要优于传统基于多尺度分解的图像融合算法。

Abstract:

The fusion result of infrared and visible images tends to become blurred, confused and suffers contrast degradation due to different characteristics of the two sources of information. To solve these problems, a fusion algorithm based on a hybrid decomposition via bilateral and Gaussian filters is proposed. Bilateral and Gaussian filters are applied firstly to achieve a hybrid decomposition for infrared and visible images. Small-scale texture details, large-scale edges and coarse image information of the input images are obtained. The sub-information is then merged to inject prominent infrared image features into the visible image, for which the fusion weights are determined according to the infrared image features represented by the decomposed large-scale edges. Finally, all the merged subinformation is assembled to reconstruct the fused image. Experiments demonstrate that the proposed fusion method obviously outperforms the image fusion algorithms based on the conventional multi-scale decomposition.