Infrared and visible image fusion based on iterative differential thermal information filter

被引:23
|
作者
Chen, Yanling [1 ,2 ,3 ]
Cheng, Lianglun [1 ,2 ,3 ]
Wu, Heng [1 ,2 ,3 ]
Mo, Fei [1 ,2 ,3 ]
Chen, Ziyang [1 ,2 ,3 ]
机构
[1] Guangdong Univ Technol, Sch Automat, Guangdong Prov Key Lab Cyber Phys Syst, Guangzhou 510006, Peoples R China
[2] Univ Arizona, Coll Opt Sci, Tucson, AZ 85721 USA
[3] Guangdong Univ Technol, Sch Comp, Guangzhou 510006, Peoples R China
基金
中国国家自然科学基金;
关键词
Infrared image; Image fusion; Infrared image enhancement; Image processing; MULTI-FOCUS; PERCEPTUAL FUSION; ALGORITHM;
D O I
10.1016/j.optlaseng.2021.106776
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
We propose an infrared and visible image fusion method based on an iterative differential thermal information filter to generate a fusion image with the salient thermal targets of the infrared image and detailed information of the visible image. Firstly, we enhance thermal information of infrared images using a dynamic threshold thermal information filter. Then, we use the multiple difference rolling guidance filter feature fusion method to separate and enhance the detailed information of the visible image. Finally, we gain the fusion image by a weighted-averaging strategy. The advantages and effectiveness of the proposed method are experimentally demonstrated by qualitatively and quantitatively comparing with the deep learning and non deep learning-based methods.
引用
收藏
页数:10
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