Fusion Algorithm of Infrared and Visible Images Based on Adaptive PCNN in NSCT Domain

In the nonsubsampled contourlet transform (NSCT) domain, an image fusion algorithm based on pulse coupled neural networks (PCNN) is proposed. Firstly, registered images to be fused are decomposed into low-pass subband and band-pass directional subbands by using NSCT. Secondly, sum-modified-Laplacian in NSCT domain is inputted to motivate PCNN whose linking strength is adaptive because of using spatial frequency in NSCT domain as the linking strength. Then, the sum of neuron firing times will generate a firing map, and coefficients of the fused image are selected from the coefficients in NSCT domain by the decision operator. Finally, the fused image is obtained by inverse NSCT. The results of simulation experiments with infrared and visible images show that the proposed algorithm has better performance than wavelet-based, NSCT-based, and typical NSCT-PCNN-based fusion algorithms.