Fusion of Infrared and Color Visible Images Based on Improved BEMD
Computer Science

Computer Science ›› 2020, Vol. 47 ›› Issue (3): 124-129.doi: 10.11896/jsjkx.190100038

• Computer Graphics & Multimedia • Previous Articles     Next Articles

Fusion of Infrared and Color Visible Images Based on Improved BEMD

ZHU Ying,XIA Yi-li,PEI Wen-jiang   

  1. (College of Information and Engineering, Southeast University, Nanjing 210096, China)
  • Received:2019-01-06 Online:2020-03-15 Published:2020-03-30
  • About author:ZHU Ying,born in 1994,postgraduate.Her main research interests include image processing. XIA Yi-li,born in 1984,professor.His research interests include statistical analysis,detection and estimation,linear and nonlinear adaptive filters,as well as their applications on communications,power systems and images.
  • Supported by:
    This work was supported by the National Natural Science Foundation of China (61771124) and Perfection Young Scholars Program of Southeast University.

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Abstract: Image fusion between the infrared and color visible images can enhance vision and improve the situation awareness.A direct use of the bidimensional empirical mode decomposition (BEMD) method for image fusion suffers from a high computation cost.Therefore,this paper proposed an improved BEMD for a fast and adaptive image fusion of infrared and color visible images.It is achieved by using order statistics filter and modified Gaussian filter to calculate the mean envelope directly,so as to accelerate the sifting process within the original BEMD.Firstly,the color visible image is transformed into IHS components.Secondly,the intensity component and the infrared image are decomposed into high frequency components and the low frequency components by means of the improved BEMD.Then,the adaptive local weighted fusion rule and the arithmetic mean rule are respectively applied to fuse the high frequency components and the low frequency components.Finally,the new intensity is transformed back into RGB.The proposed image fusion scheme is not only fast but also able to achieve the best fusion result,which merges edge details in the infrared image and the spectral information in the color visible image well.

Key words: Adaptive local weighted fusion rule, BEMD, Gaussian filter, Image fusion, Order statistics filter

CLC Number: 

  • TP391
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