Underwater imaging is a challenging task due to the presence of scattering and absorption caused by suspended particles in water. These factors result in hazy and low-contrast images that make it difficult to extract useful information. In this paper, we propose an underwater image dehazing approach based on the attenuation of artificial light. Our method estimates the transmission map of the scene using the light attenuation and then uses it to recover the clear image from the hazy observation. To estimate the transmission map, we use underwater image pairs with adaptively adjusted artificial light levels, and solve for the unknown attenuation coefficient and transmission values. The estimated transmission map is then used for extracting the backscatter and removing the haze from the image. We evaluate our method on a dataset of hazy and clear underwater image pairs and show that it outperforms state-of-the-art methods in terms of visual quality and quantitative metrics such as the peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM).