Light scattering and color shift are two major sources of distortion for underwater photography. Light scattering is caused by light incident on objects reflected and deflected multiple times by particles present in the water before reaching the camera. This in turn lowers the visibility and contrast of the image captured. Color shift corresponds to the varying degrees of attenuation encountered by light traveling in the water with different wavelengths, rendering ambient underwater environments dominated by bluish tone. This paper proposes a novel approach to enhance underwater images by a dehazing algorithm with wavelength compensation. Once the depth map, i.e., distances between the objects and the camera, is estimated by dark channel prior, the light intensities of foreground and background are compared to determine whether an artificial light source is employed during image capturing process. After compensating the effect of artifical light, the haze phenomenon from light scattering is removed by the dehazing algorithm. Next, estimation of the image scene depth according to the residual energy ratios of different wavelengths in the background is performed. Based on the amount of attenuation corresponding to each light wavelength, color shift compensation is conducted to restore color balance. A Super-Rsolution image can offer more details that must be important and necessary in low resolution underwater image. In this paper combine Gradient-Base Super Resolution and Iterative Back-Projection (IBP) to propose Cocktail Super Resolution algorithm, with the bilateral filter to remove the chessboard effect and ringing effect along image edges, and improve the image quality. The underwater videos with diversified resolution downloaded from the Youtube website are processed by employing WCID, histogram equalization, and a traditional dehazing algorithm, respectively. Test results demonstrate that videos with significantly enhanced visibility and superior color fidelity are obtained by the WCID proposed.