In order to make the fusion image of visible and infrared better express the target information, the non-subsampled Shearlet transform and split strategy are combined to fuse them. First of all, the high and low frequency components of visible and infrared images are obtained by using the non-sampling shearlet transform. Then, the Otsu thresholding segmentation method is used to develop the stripping strategy for ping the target layer and its background layer of infrared image. Based on the target layer, the low-frequency coefficients of the background layer of the visible image and the infrared image are weighted by using the regional energy characteristics of the image, and the result is combined with the target layer of the infrared image to obtain the fusion low-frequency coefficients which are rich in the target content and background content. The regional variance function is introduced to measure the detail features of the image, and by constructing the variance weighting factor, the fusion high-frequency coefficient which riched in detail features is obtained. Finally, the non-subsampled Shearlet inverse transform is applied to the two fusion coefficients for outputting the fused image. The experimental results show that the fusion image of this algorithm has better target and detail expression ability than the existing fusion image, which can be used to obtain high-quality visible and infrared fusion image.