Journal of Jilin University Science Edition ›› 2021, Vol. 59 ›› Issue (3): 595-601.

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Fusion Method Based on Content Enhancement for Visible-Infrared Image

FENG Fucun, CHANG Lihong   

  1. School of Mathematics and Computer Science, Ningxia Normal University, Guyuan 756099, Ningxia Hui Autonomous Region, China
  • Received:2020-05-13 Online:2021-05-26 Published:2021-05-23

Abstract: In order to better preserve the rich details of the visible image, we proposed a dynamic image compression enhancement method based on directional guided wave to fuse visible image and infrared image. Firstly, the directional guided wave enhancement method was used to enhance the visible image. Secondly, a low-frequency subband and a series of high-frequency subbands were obtained by decomposing the enhanced visible image and the corresponding infrared image with the nonsubsampled contourlet. A sparse representation theory was used to fuse the low-frequency subband. The parametric adaptive impulse coupled neural network was used to fuse each high-frequency subband. Finally, the fused image was obtained by the inverse transform of nonsubsampled contourlet. The experimental results show that the proposed method is superior to the traditional methods in objective quality evaluation and visual inspection.

Key words: image fusion, nonsubsampled contourlet, sparse representation, impulse neural network

CLC Number: 

  • TP391.41