Underwater Image Restoration Based on Total Variation and Color Balance

Aiming at solving the problems of fogging, blurring and color distortion in underwater images, an underwater image restoration method is proposed based on total variation and color balance. Depending on the complete underwater optical imaging model, the background light is estimated by combining the quadtree subdivision algorithm and the propagation characteristics of light in water, the transmittance is estimated by using the underwater median dark channel prior, and the fuzzy kernel is estimated by using the conjugate gradient and iterative least square method. In order to improve the computational efficiency, the alternating direction multiplier method is introduced to inverserly solve the variational energy equation to obtain a haze-free and deblurred image. In addition, a color balance algorithm is proposed to compensate color channel in YCbCr space for correcting color distortion. Compared with six popular underwater image enhancement and restoration methods, the experimental results show that the proposed method can effectively remove fog and blur, correct color deviation, and restore a clear and true color underwater image.