As infrared image enhancement method based on wavelet transformation has the problem of unperfect visual effect, and Retinex enhancement algorithm can enhance visual effect of the image by improving brightness uniformity, a method based on stationary wavelet transformation and Retinex is proposed. Firstly, the infrared image is decomposed into high-frequency detail and low-frequency approximation components at various resolutions, and the low frequency subband image of the largest scale is enhanced by multiscale Retinex algorithm. Then, the high-frequency subband images are denoised by Bayesian shrinkage method, and the gain coefficients of high-frequency subbands are available by calculating the local contrast of the enhanced low-frequency subband based on fuzzy rules to get the enhanced high-frequency subband images. Finally, the enhanced image is reconstructed by the low-frequency subband and high-frequency subbands. Experiments with qualitative and quantitative evaluation are carried out for many images, and the proposed method is compared with histogram double equalization method, second generation wavelet transform method, curvelet transform method, and multiscale Retinex method. Experimental results show that the proposed method can enhance image details and suppress noise better, and the whole visual effect is improved significantly.