Underwater image restoration via background light estimation and depth map optimization.

In underwater images, the significant sources of distortion are light attenuation and scattering. Existing underwater image restoration technologies cannot deal with the poor contrast and color distortion bias of underwater images. This work provides a new underwater image restoration approach relying on depth map optimization and background light (BL) estimation.

Underwater image restoration by red channel compensation and underwater median dark channel prior.

Underwater images often show low contrast, blurring, and color distortion due to the absorption and scattering of light. In contrast to existing underwater image restoration methods, we propose an underwater image restoration method with red channel compensation and blue-green channel restoration. First, a proposed approach relies on the hue and attenuation differences between different color channels of the underwater image to estimate the background light.