In hue, saturation and value (HSV) color space, an effective remote sensing image fusion algorithm is proposed combining with simplified pulse coupled neural network (S-PCNN) and two-dimensional stationary wavelet transform (SWT). The multispectral transformed into HSV color space, the multispectral V component and the panchromatic spectrum are decomposed by two-dimensional static wavelet decomposition, and the decomposed high-frequency coefficients is put into S-PCNN model to fuse.The low-frequency coefficients are decomposed second time and fused with different rules, the fused V component is obtained through wavelet inverse transformation for fused wavelet coefficient, the multispectral H, S components and fused V component are transformed into RGB space. Through a group of common remote sensing images experiment, the results show that the fusion effects of proposed algorithm is better than the traditional algorithms, and the fused image contains lots of detail, color. It is an effective remote sensing image fusion algorithm.