LAUSR

Object identification in highly turbid optical media depends mainly on the quality of collected images. Underwater images acquired in a turbid environment are generally of very poor quality. Attenuation and backscattering of light by water, by materials dissolved in the water, and by particulate material are the main causes of the degradation of underwater images. It is therefore essential to improve the quality of such images to facilitate object identification. The focus of this paper is to report the principle and validation of a fast and effective method of improving the quality of underwater images. On the one hand, this method uses a polarimetric imaging optical system to reduce the effect of diffusion on the image acquisition. On the other hand, it is based on an optimized version of the dark channel prior (DCP) method that has received a great deal of attention for image dehazing. Results derived from images obtained in a controlled laboratory water tank environment with different turbidity conditions and images from tests using the proposed method at sea demonstrate an ability to significantly improve visibility and reduce runtime by a factor of about 50 for a 4K image when compared to conventional DCP methods.