An Enhancement Method for Underwater Images under Natural Illumination Based on Scene Depth Estimation

To address the problems of blur, low contrast and color cast in underwater images, an enhancement method for underwater images under natural illumination based on scene depth estimation is proposed by combining the refined underwater imaging model. Firstly, the brightness information of an image is used to estimate the scene depth by minimum filtering and soft matting method, according to the prior theory that the brightness of the underwater scene under natural illumination conditions is generally proportional to its scene depth. Secondly, the backscatter of some discrete pixels is estimated by using the dark channel prior and the scene depth information, and then the backscatter in the whole image is fitted and removed by combining the refined underwater imaging model. On this basis, the chromatic-adaptation-based color correction method is applied to the direct component of the image to remove the color cast. In addition, the linear stretching method is adopted to improve the brightness and contrast of the restored image. The experiment results in various underwater scenes show that the proposed method can effectively remove the foggy blur caused by backscatter, and improve the contrast and correct the color cast of underwater images.