The work aims to propose a method of infrared and visible image fusion based on NSST and SWT for the missing of fine features in the fusion results of infrared and visible images based on NSST, so as to improve the quality of fused image. Firstly, the infrared and visible images were decomposed by NSST to obtain a low frequency coefficient and multiple high frequency coefficients in different directions and scales, respectively. Then the two low frequency coefficients were decomposed by SWT to obtain the new low frequency coefficients and the high frequency coefficients respectively. The new low frequency coefficient and high frequency coefficient obtained by SWT decomposition separately adopted the linear weighted average method and the region average energy to increase the fusion strategy. The fusion result of low frequency coefficient was obtained by SWT inverse transform, and the high frequency coefficient was fused by the fusion strategy with large region average energy. Finally, the final fusion image was obtained by NSST inverse transform. The simulation fusion results showed that the proposed algorithm was more obvious in visual infrared target and clearer in detail and was also the best in evaluation index such as IE, AG, QAB/F, SF and SD, when compared with NSST, SWT, NSCT, et al. The fusion result of this algorithm can better express the target information and the detailed texture information of the source images, so this algorithm has the superiority.