A Novel Multi-focus Image Fusion Method Using NSCT and PCNN

  • Zhuqing JiaoEmail author
  • Jintao Shao
  • Baoguo Xu
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 165)


Considering multi-focus images from the same scene, a fusion method using pulse-coupled neural network in non-subsampled Contourlet transform domain is proposed. The input images are performed to multi-scale and multi-direction NSCT decomposition, then both the low-pass subband coefficients and the band-pass directional subband coefficients are input into PCNN. The ignition mapping images are obtained via the ignition frequency generated by neuron iteration. With the neighborhood approach degree of ignition frequency, corresponding subband coefficients are selected and the fused result is obtained through inverse NSCT. Experimental analysis demonstrates that the proposed method retains clear regions and feature information of multi-focus images on a greater degree and has better fusion performance than other existing methods.


image fusion multi-focus image non-subsampled Contourlet transform pulse-coupled neural network 


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Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.School of Communication and Control EngineeringJiangnan UniversityWuxiChina

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