Depth estimation for underwater images from single view image

Abstract

Underwater images often undergo distortions from scattering, absorption, colour loss, diffraction, polarisation, and varying attenuation depending on the light frequency, due to the water medium. This study answers problems associated with the recovery of underwater images, by developing novel depth map estimation which may be used as an intermediary step for underwater image restoration. The depth map is an important factor for the recovery of the underwater image, as it has been shown that proper estimation of depth, results in better restoration of the underwater image. The proposed algorithm estimates a depth map from a single view image, using blurriness and lighting information, obtained using a simple background neutralisation method. Results from the algorithm on selected raw underwater image data set have been compared with other algorithms and it has been shown that the proposed method gives Pearson coefficients in the range of 0.75–0.95, which are considerably higher and better log root mean square value compared to other methods in the literature. This suggests a better estimation of depth by the proposed method.