A novel multi-sensor image fusion method based on multi-objective particle swarm optimization is proposed to solve the parameter optimization problem in the image fusion. Firstly, the Nonsubsampled Contourlet Transform (NSCT) is used to perform multi-scale and multi-directional decomposition on the source images. Then select the objective evaluation criteria as the optimal objective function. Multi-objective particle swarm optimization algorithm is used to optimize the fusion parameters of low-frequency coefficients. For band-pass directional sub-band coefficients selection, the rule of maximum absolute value is used. Finally, the fused image is obtained through inverse transform. The algorithm has been used to merge multi-focus images and infrared and visible light images. The experimental results indicate that the fused image obtained by the proposed method has a better subjective visual effect and objective evaluation criteria.