Underwater Image Enhancement Strategy with Virtual Retina Model and Image Quality Assessment

Underwater image enhancement is one of the most essential and fundamental tasks in ocean investigations recent years. In this paper, we made an attempt to develop one adaptive underwater image enhancement approach with the help of the virtual retina model and the image quality assessment (IQA). The virtual retina model, which yields comparatively high correlation with the human vision system, is first taken to achieve simultaneous ambiguity removing and detail enhancing of single image due to the specific mechanisms of different retinal sub-layers. After this, an adaptive image enhancement strategy is taken with one kind of no-reference image quality assessment based Patch Discrete Cosine Transform (PDCT), which indicates whether the image patches are naturally uniform or not. It is shown in the simulation experiment that the proposed approach could achieve great performances in both robustness and effectiveness, with good behaviors in the vision effects and precision for the underwater images.