A novel algorithm for image fusion was put forward. Based on lifting wavelet transform, the nonsampled lifting wavelet transform with the trait of shift invariance was obtained by cancelling the odd and even split process of lifting wavelet transform. When the source images were decomposed by the nonsampled lifting wavelet transform, the spatial frequency ratio for the low-frequency was defined. Then the low-frequency coefficients were fused by means of the combination of weighting and selection, fusion genes for the low-frequency field were computed by corresponding regional spatial frequency ratio, and the high- frequency was fused by weighting fusion algorithm based on edge. Finally, the fused image was obtained through inverse nonsampled lifting wavelet transform reconstruction. The experimental results show that the proposed image fusion algorithm could describe the grey discontinuous information in a better way. Moreover, compared with traditional algorithms, obtained fused images contain more abundant details with features.