Aiming at the phenomenon of color attenuation, surface blur, and uneven illumination in underwater optical images, we proposed an underwater optical image enhancement algorithm based on color constancy and multiscale wavelet. First, we adopt the gray world assumption to compensate the attenuation channel and use the color constancy to adaptively adjust the global brightness and contrast of the image to effectively correct the color shift. Second, combined with the characteristics of multiscale wavelet decomposition, we adopt morphological open operation to improve the dark channel transmittance to remove the low-frequency haze phenomenon, and the soft threshold reduces the high-frequency noise. Then, a two-dimensional gamma function is used to adaptively correct the uneven illumination, and sharpening is used to improve the edge detail. Finally, the weight map of the fused input image is defined: gamma correction and sharpening images, and the enhanced image is obtained by multiscale fusion. The experimental results show that the proposed algorithm can effectively balance the chromaticity and brightness of underwater optical images and significantly improve image clarity and detail information. Additionally, application tests show that the algorithm performs well in feature matching, low-light conditions, and edge detection.