Underwater image restoration by red-dark channel prior and point spread function deconvolution

In the field of undersea research, underwater vehicles usually carry camera systems for recording. The captured image or video often has two undesired characteristics: color distortion and low visibility. This is because that the light is exponentially attenuated while penetrating through water. Furthermore, the quality of attenuation is associated with the wavelength of spectrum. This paper simplifies the Jaffe-McGlamery optical model and proposes an effective algorithm to recover underwater images. In our approach, a red-dark channel prior was defined and derived to estimate the background light and the transmission. The visibility of scene was compensated by the object-camera distance to recover the colors of the background and objects. Subsequently, by analyzing the physical property of the point spread function, we developed a simple but efficient low-pass filter to deblur degraded underwater images. A wide variety of underwater images with different scenarios were used for the experiments. The experimental results indicated that the proposed algorithm effectively recovered underwater images while eliminating the influence of absorption and scattering. We believe that this new restoration algorithm is promising in many underwater image processing applications.