Acquisition of clear and accurate underwater images is an important prerequisite to help people explore the underwater world. However， compared with regular images， underwater images always have problems such as low contrast， detail loss and color distortion， resulting in bad visual effect. In order to solve the problems， a new underwater image enhancement algorithm based on Artificial Under-exposure Fusion and White-Balancing technique （AUF+WB） was proposed. Firstly， the Gamma correction operation was used to process the original underwater image and generate 5 corresponding under-exposure images. Then， the contrast， saturation and well-exposedness were employed as fusion weights， and the multi-scale fusion method was combined to generate the fused image. Finally， the images compensated by various color channels were combined with the Gray-World white balance assumption respectively to generate the corresponding white balance images， and these obtained white balance images were evaluated by using the Underwater Color Image Quality Evaluation （UCIQE） and the Underwater Image Quality Measure （UIQM）. With selecting different types of underwater images as experimental samples， the proposed AUF+WB algorithm was compared with the existing state-of-the-art underwater image defogging algorithms. The results show that， the proposed AUF+WB algorithm has better performance than the comparison algorithms on both qualitative and quantitative analysis of image quality. The proposed AUF+WB algorithm can effectively improve the visual quality of underwater images by removing color distortion， enhancing contrast， and recovering details of underwater images.