Multiple aperture underwater imaging algorithm based on polarization information fusion

Abstract

Underwater optical imaging is the key technology to explore the underwater mystery. However, due to the absorption and backscattering effects of the media in the underwater environment, the image acquired by the detector will be severely degraded. In order to obtain the effective underwater scene information, it is necessary to restore the acquired underwater image. The restoration technology based on differential polarization is one of the main methods of restoring the underwater images, which can suppress the background scattered light by the common-mode suppression between orthogonal polarization graphs, thus realizing the restoration of underwater image. However, the relevant research shows that the restoration effect of this method is general for the underwater non-uniform light field. The main reason is that the estimation errors of polarization degree and background scattering intensity under the condition of the non-uniform underwater light field are large. Out of the above problem, in this paper we present the multiple aperture underwater imaging technology of fused polarization information. The method uses the camera array to realize the large virtual aperture imaging system, thus obtaining the wide-angle light field information, and then to fuse the depth information of the scene to realize the accurate estimation of background scattering light intensity and polarization degree under the condition of underwater non-uniform light field. The estimated parameter value can better reflect the global characteristics of the scene. Through the imaging experiments on the targets with different polarization degrees in the turbid underwater environment, comparing with the current advanced restoration algorithm, the results show that the proposed method can effectively solve the problems of background scattering and polarization degree significant estimation error caused by non-uniform underwater light field, and obtain high-quality restoration results. Through the contrast imaging experiment of the target in the underwater environment with different turbidity concentrations, the results show that with the increase of turbidity concentration of the water, the image recovery effect of the method in this paper is gradually weakened. However, it still has a good restoration effect at a large concentration. At the same time, imaging experiments are conducted on targets in underwater environments with different sediment concentrations. The results show that the method proposed in this paper can also obtain a better restoration image in the turbid water environment containing sediment.