Aiming at the characteristics of the infrared and visible image fusion,a fusion method that can reduce the algorithm complexity,based on the Non-subsampled Shearlet Transform(NSST)and the Compressed Sensing(CS)is proposed.The source images are decomposed sparsely on multi-direction and multi-scale by using NSST,and then the low-frequency coefficients and every bandpass subband direction coefficients are obtained respectively.For the low frequency subband coefficients,the fusion method of the weighted average based on the target characteristics is adopted;Compressed sensing measurement matrix uses the fast Walsh Hadad matrix.For the bandpass subband coefficients,the fusion method based on the region variance to choose big one is adopted.The measured fusion values are reconstructed by using the recovery algorithm based on the augmented Lagrange multiplier and overlapping direction,and then the approximate precision values of the band pass subband coefficients are achieved.Experimental results show that the fusion method can guarantee the sharpness of the fused image and reduce the running time of the algorithm.