For the problems of definition difference and poor texture information of image after infrared (IR) and visible (VIS) light image fusion within multiscale transform domain, an improved fusion algorithm for IR and VIS images based on shearlet transform(ST) is proposed. Firstly, Morphology-Hat transform is used for an IR and a VIS light image separately. Then the enhanced IR and VIS light image are decomposed into high-frequency and low-frequency images by shearlet transform(ST). For the high frequency image, the fusion strategy of a local variance and the absolute value of the coefficient is proposed. For the low frequency image, a new weighted fusion strategy is proposed. Finally, the fused image is obtained by using the inverse shearlet transform(IST). The simulation experimental results show that the proposed method has superior performance.