We propose a Retinex image enhancement algorithm based on image fusion technology to overcome the disadvantages of halo phenomenon and grey phenomenon of the singlescale Retinex algorithm. For the halo phenomenon, the illumination image of an original image is estimated by Gaussian weighted bilateral filtering instead of Gaussian kernel function, which can remove the halo phenomenon effectively. For the problem of grey, the image fusion technology is introduced into the process of image enhancement. Here are the several steps of the proposed algorithm. In the first place, the reflection image is stretched by nonlinear transformation and the bright and dark areas of the stretched image are determined by the Otsu threshold segmentation algorithm. Then the optimal image for bright areas and the optimal image for dark areas are obtained by adjusting the parameters of nonlinear transformation according to information entropy, and the original image, the optimal image for bright areas and the optimal image for dark areas are fused by the optimal fusion algorithm. Finally, a consistency verification method is introduced to remove the blocking effect caused by the optimal fusion algorithm. Experimental results show that the new algorithm can get the details of an image, remove the halo phenomenon and overcome the grey problem effectively. It also has a better ability to enhance images compared with the singlescale Retinex algorithm, Retinex algorithm based on bilateral filtering, histogram equalization and unshaped mask algorithm.