Computer Science ›› 2018, Vol. 45 ›› Issue (12): 217-222.doi: 10.11896/j.issn.1002-137X.2018.12.036

• Graphics, Image & Pattern Recognition • Previous Articles     Next Articles

Multi-focus Image Fusion Method Based on NSST and Adaptive PCNN

YANG Li-su, WANG Lei, GUO Quan   

  1. (College of Computer Science and Technology,Shandong University of Technology,Zibo,Shandong 255000,China)
  • Received:2017-11-04 Online:2018-12-15 Published:2019-02-25

Abstract: In order to overcome the disadvantages of low fusion quality in traditional image fusion methods,this paper proposed an image fusion method based on the nonsubsampled shearlet transform (NSST) and adaptive pulse coupled neural network (PCNN).Firstly,the source image is decomposed by nonsubsampled shearlet transform.Then,the low frequency fusion of the obtained low frequency components is performed by using the fusion rule based on the guided image filter.After that,the improved spatial frequency is used as the PCNN input for the high frequency component,and the improved Laplace energy summation is used as the PCNN link strength of PCNN.Finally,the fused image is obtained by inversion of NSST.The experimental results show that this algorithm can preserve the details well and prevent product artifacts and distortions from the perspective of subjective effects,and it possesses more superior perfor-mance in terms of objective indicator,such as standard deviation,QAB/F,entropy and mutual information.

Key words: Guided image filter, Image fusion, Nonsubsampled shearlet transform, Pulse coupled neural network

CLC Number: 

  • TP391.41
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