Journal of Systems Engineering and Electronics ›› 2013, Vol. 35 ›› Issue (4): 720-724.doi: 10.3969/j.issn.1001-506X.2013.04.07

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Image fusion based on region and directional variance weighted entropy

GUO Ming1, WANG Shu-man2
  

  1. 1. Department of Electronics and Information, Naval Aeronautical and Astronautical University, Yantai 264001, China; 2. Naval Academy of Armament, Beijing 100161, China
  • Online:2013-04-17 Published:2010-01-03

Abstract:

A fusion algorithm for infrared and visible images based on nonsubsampled Contourlet transform (NSCT) is proposed. Firstly, the infrared image is segmented to target region and background region, which is also mapped to the visible image. Secondly, the NSCT is performed on the infrared and visible image at different scales and different directions. In the target region, the low-frequency coefficients of the fusion image are selected with those of infrared image, and in the background region the low-frequency coefficients of the fusion image are selected with those of visible image. The high-frequency coefficients are fused with a rule of the maximum directional variance weighted entropy. Finally, the fused coefficients are reconstructed to obtain the fused image. The experimental results show that the proposed image fusion algorithm gets more image detail in the information, the amount of information increases significantly, and the target detection in the fused image becomes simpler.

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