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This paper presents an improved dual channel pulse coupled neural network(IDC-PCNN) model for image fusion. The model can overcome some defects ofstandard PCNN model. In this fusion scheme, the multiplication rule is replacedby addition rule in the information fusion pool of dual channel PCNN (DC-PCNN)model. Meanwhile the sum of modified Laplacian (SML) measure is adopted, whichis better than other focus measures. This method not only inherits the goodcharacteristics of the standard PCNN model but also enhances the computingefficiency and fusion quality. The performance of the proposed method isevaluated by using four criteria including average cross entropy, root meansquare error, peak value signal to noise ratio and structure similarity index.Comparative studies show that the proposed fusion algorithm outperforms thestandard PCNN method and the DC-PCNN method.

Improved dual channel pulse coupled neural network and its application to multi-focus image fusion