A multi-wavelet system with detailed mathematical expression called V-system is introduced.The infrared and visible images are decomposed into different layers and orientations by using multi-resolution of V-system and multi-orientation in non-subsampled contourlettransform(NSCT).And then different fusion strategies were adopted to fuse raw images in each layer and each orientation respectively.Firstly,the original image was decomposed by multi-level V-decomposition,and contour informations and multi-layer detailed informations of images were gotten;then the obtained contour informations were decompose again by NSCT to obtain low frequency and high frequency coefficients.The low frequency coefficients are fused according to the strategy based on sparse representation,and the high frequency coefficients are fused according to the strategy based on 2D Log-Gabor energy,and then the improved pulse coupled neural network was used to fuse multi-layer detailed information.Finally,the fused image is obtained by the corresponding inverse transformation.The algorithm decomposes images in different layers and orientations to obtain more refined detail of raw images.The combination of various fusion strategies makes the detailed information more clear and enhances the contrast of the fused images,and it also improves the objective indicators observably.