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In traditional infrared and visible image fusion results, target is tend to be weakened and details of background are blurred. To solve these problems, a new fusion algorithm based on bilateral filters and non-subsampled shearlet transform (NSST) is proposed. Firstly, bilateral and Gaussian filters are applied in source images to obtain the image which includes large-scale edges and infrared target information. Then, the source images are decomposed into low and high frequency sub-bands by NSST. The image with large-scale edges is used to guide the fusion of the low frequency sub-band, and the rule of maximum absolute value selection is used for the fusion of high frequency sub-bands. Finally,Sperform the inverse transform in order to obtain the final fusion result. Experiments demonstrate that the proposed fusion method can obviously highlight the target area, preserve details of the background area, and the quality evaluation indexes including entropy, mutual information, and peak signal to noise ratio is increased compared with conventional algorithnm.