A self-adaptive underwater image enhancement algorithm is proposed to address the issues of color distortion, decreased contrast, and blurring caused by the imaging environment in underwater images. First, based on the local and global color biases in the Lab color space, color compensation is applied to attenuated colors, and thereafter the grayscale world algorithm is used to restore the color balance of underwater images. Second, automatic color scale and gamma correction methods are used to adjust the information of each channel to obtain images with high dynamic range and high illumination. Finally, high-frequency information is obtained through the antisharpening mask method, and image details are enhanced to obtain clear underwater images. The proposed algorithm utilizes statistical information, such as the color deviation and mean square deviation of the image, to achieve adaptive processing. The experimental results show that the proposed algorithm can effectively remove color deviation from underwater images, improve image contrast and clarity, and enhance visual effects. Compared with other algorithms, it has advantages in processing efficiency and time.