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《Acta Optica Sinica》 2017-08
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Infrared and Visible Image Fusion Based on Target Extraction and Guided Filtering Enhancement

Wu Yiquan;Wang Zhilai;College of Electronic and Information Engineering,Nanjing University of Aeronautics and Astronautics;Jiangsu Key Laboratory of Big Data Analysis Technology,Nanjing University of Information Science &Technology;Zhejiang Province Key Laboratory for Signal Processing,Zhejiang University of Technology;Guangxi Key Lab of Multi-Source Information Mining and Security,Institute of Mineral Resources,Guangxi Normal University;Key Laboratory of Geo-Spatial Information Technology,Ministry of Land and Resources,Chengdu University of Technology;Key Laboratory of Metallogeny and Mineral Assessment,Institute of Mineral Resources,Ministry of Land and Resources,Chinese Academy of Geological Sciences;  
In order to highlight the fusion result and dig out more details,a fusion method of infrared image and visible image based on the target extraction and guidance filtering enhancement is proposed.Firstly,the twodimensional Tsallis entropy and graph-based visual saliency model are used to extract the target region of infrared image.Then the visible image and the infrared image are decomposed by non-subsampled shearlet transform(NSST),respectively.The low-frequency components of the visible image and the infrared image are enhanced with guided filtering,respectively.The low-frequency component of the fused image is obtained from the enhanced lowfrequency component of the infrared image and the visible image based on the fusion rule of target extraction,and the high-frequency components of the fused image are gained according to the maximization criterion of the directional sub-band information sum.Finally,the fused image is obtained by inverse NSST transform.A large number of experimental results demonstrate that the proposed method can improve the spatial resolution of the fused image,effectively highlight the target,and is superior to the method based on the Laplacian pyramid transform,the method based on wavelet transform,the method based on stationary wavelet transform,the method based on nonsubsampled contourlet transform(NSCT),the method based on target extraction and NSCT in the quantitative evaluation indexes such as information entropy and average gradient.
【Fund】: 国家自然科学基金(61573183);; 南京信息工程大学江苏省大数据分析技术重点实验室开放基金资助(KXK1403);; 浙江省信号处理重点实验室开放基金(ZJKL_6_SP-OP2014-02);; 广西多源信息发掘与安全重点实验室开放基金(MIMS16-01);; 成都理工大学国土资源部地学空间信息技术重点实验室开放基金(KLGSIT2015-05);; 国土资源部成矿作用与资源评价重点实验室开放基金(ZS1406);; 江苏高校优势学科建设工程
【CateGory Index】: TP391.41
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