In order to improve the efficiency of image fusion and maintain good edge support so as to better complete image reconstruction, an image fusion algorithm based on wavelet transform was proposed. The advantages of multidirectional feature extraction of signals using wavelet transform could simplify the analysis of multidimensional image signals. In the formulation of fusion rules, the clarity of the image fusion and the complexity of the fusion algorithm are weighed, and the lowfrequency signal and the highfrequency signal of the image signal are processed separately. Lowfrequency weighted average, highfrequency local variance processing, and finally wavelet inverse transform to get the reconstructed image. Experimental results show that this method has a clear effect on reconstructing images and it has a high signaltonoise ratio.