The work aims to propose an image fusion algorithm based on Non-Subsampled Direction Filter Bank (NSDFB) coupling local Laplacian energy sum, regarding the fusion algorithm based on the Contourlet transform that easily leads to the Gibbs phenomenon on the edge. Firstly, combined with multi-wavelet transform (MWT) and NSDFB, the image was decomposed into three high frequency directional coefficients and one low frequency coefficient. Then, for low frequency coefficient, the LSML-PCNN model composed of Local Sum-Modified-Laplacian (LSML) and pulse couple neural network (PCNN) was used to fuse the low frequency information. For the high frequency coefficient, the low frequency and high frequency subband edges were extracted, and the absolute maximum value method of coefficient was used as the basis to achieve the fusion of high frequency coefficients. The experimental results showed that, the proposed algorithm had higher fusion quality and clearer and more complete edges of the fusion image than the current image fusion scheme. The proposed algorithm has a higher fusion visual effect and it can improve the contrast and resolution of images, which has certain reference value in the field of image processing.