Traditional image fusion based on multi-scale transform experiences problems such as low contrast and edge details. A fusion algorithm based on the adaptive fuzzy logic and an adaptive pulse coupled neural network (PCNN) is proposed in the nonsubsampled contourlet transform domain. For the low-frequency sub-band, the fusion is based on the adaptive fuzzy logic. For the high-frequency sub-band, the information about orientation is adaptively utilized as the linking strength of the PCNN and the edge features of the source images are adopted as the input to motivate the adaptive PCNN. Then, the sub-band coefficient is fused according to the pulse ignition amplitude. The experimental results indicate that the proposed fusion algorithm can better highlight the target information of the fusion image, provide richer background details, and achieve a better fusion effect both on the clarity of fusion images and the human vision.