Dehazing and deblurring of underwater images with heavy-tailed priors

Abstract

The common problems of underwater images include color cast, haze effect, and the motion blur effect caused by turbulence and camera shake. To address these problems, research on color cast and haze and blur effects is carried out in this paper. Because red light has significant attenuation underwater, which could cause color cast of images, this paper proposes a red channel compensation method to solve this problem. This approach adaptively compensates for the red channel according to the pixel value of the red channel, successfully preventing excessive compensation. To address the haze effect of underwater images, combined with the physical model of underwater images, a variational method is introduced in the paper. This method can not only recover clear underwater images, but also refine the transmission map at the same time. Furthermore, the blind deconvolution method is adopted to deblur underwater images. First, the blur kernel of an underwater image is estimated, and then a clear underwater image is recovered based on the obtained blur kernel. Finally, qualitative and quantitative comparisons of the underwater images recovered by different methods are also carried out. From the qualitative perspective, the images recovered by our method have higher image sharpness and more outstanding details. The quantitative comparison results show that the images recovered using our method have higher scores according to various criteria. Therefore, on the whole, our method presents great advantages in comparison with others.