Journal of Systems Engineering and Electronics ›› 2019, Vol. 30 ›› Issue (5): 831-840.doi: 10.21629/JSEE.2019.05.02

• Electronics Technology • Previous Articles     Next Articles

Multi-source image fusion algorithm based on fast weighted guided filter

Jian WANG1,2,*(), Ke YANG1(), Ping REN1(), Chunxia QIN1(), Xiufei ZHANG1()   

  1. 1 School of Electronics and Information Engineering, Northwestern Polytechnical University, Xi'an 710072, China
    2 No. 365 Institute, Northwestern Polytechnical University, Xi'an 710065, China
  • Received:2018-11-12 Online:2019-10-08 Published:2019-10-09
  • Contact: Jian WANG E-mail:jianwang@nwpu.edu.cn;yk@mail.nwpu.edu.cn;1403147639@mail.nwpu.edu.cn;qin@163.com;921391314@qq.com
  • About author:WANG Jian was born in 1972. He received his Ph.D. degree in signal and information processing from the Northwestern Polytechnical University in 2005. Now he is an assistant professor at the School of Electronics and Information, Northwestern Polytechnical University, Xi'an, China. His current research interests include UAV intelligent processing technology, UAV ground observation video signal processing technology, and multi-source information intelligent processing technology. E-mail: jianwang@nwpu.edu.cn|YANG Ke was born in 1995. She received her B.S. degree in electronic and information engineering from Taiyuan University of Technology in 2017. She is currently pursing her M.S. degree in the School of Electronics and Information, Northwestern Polytechnical University, Xi'an, China. Her research interests include signal processing and image fusion. E-mail: xgdms yk@mail.nwpu.edu.cn|REN Ping was born in 1993. She received her B.S. degree in electronic and information engineering from Northwestern University in 2016. She is now pursing her M.S. degree in the School of Electronics and Information, Northwestern Polytechnical University, Xi'an, China. Her research interests include signal processing and target recognition. E-mail: 1403147639@mail.nwpu.edu.cn|QIN Chunxia was born in 1995. She received her B.S. degree in electronic and information engineering from Northwestern Normal University in 2017. She is now pursing her M.S. degree in the School of Electronics and Information, Northwestern Polytechnical University, Xi'an, China. Her research interest is signal processing. E-mail: chunxia qin@163.com|ZHANG Xiufei was born in 1989. He received his M.S. degree from the School of Electronics and Information Engineering, Northwestern Polytechnical University in 2017. He is now pursing his Ph.D. degree in the School of Automation, Northwestern Polytechnical University, Xi'an, China. His research interests include signal processing and image fusion. E-mail: 921391314@qq.com
  • Supported by:
    the National Natural Science Foundation of China(61472324);the National Natural Science Foundation of China(61671383);Shaanxi Key Industry Innovation Chain Project(2018ZDCXL-G-12-2);Shaanxi Key Industry Innovation Chain Project(2019ZDLGY14-02-02);This work was supported by the National Natural Science Foundation of China (61472324; 61671383), and Shaanxi Key Industry Innovation Chain Project (2018ZDCXL-G-12-2; 2019ZDLGY14-02-02)

Abstract:

In last few years, guided image fusion algorithms become more and more popular. However, the current algorithms cannot solve the halo artifacts. We propose an image fusion algorithm based on fast weighted guided filter. Firstly, the source images are separated into a series of high and low frequency components. Secondly, three visual features of the source image are extracted to construct a decision graph model. Thirdly, a fast weighted guided filter is raised to optimize the result obtained in the previous step and reduce the time complexity by considering the correlation among neighboring pixels. Finally, the image obtained in the previous step is combined with the weight map to realize the image fusion. The proposed algorithm is applied to multi-focus, visible-infrared and multi-modal image respectively and the final results show that the algorithm effectively solves the halo artifacts of the merged images with higher efficiency, and is better than the traditional method considering subjective visual consequent and objective evaluation.

Key words: fast guided filter, image fusion, visual feature, decision map