Aiming at the shortcomings of the traditional NSCT image fusion algorithm, we propose an image fusion algorithm based on complementary wavelet transform and PCNN in NSCT domain. Firstly, we use the NSCT to decompose the source image and generate a series of low frequency and high frequency subbands. Low frequency subbands are decomposed by twodimensional wavelet into a low frequency subband and three directional subbands. Then the low frequency subband is fused by the local region energy weighting method. And the three directional subbands are fused by the improved Gaussian weighted SML method. The high frequency subbands decomposed by the NSCT are divided into the highest layers and other layers for fusion. The highest layers are fused by using the improved Gaussian weighted SML method, and the other layers are fused by the PCNN method enhanced by edge gradient information. Finally, the fused image is obtained through NSCT inverse transform. Experimental results demonstrate the effectiveness of the proposed algorithm.