A novel adaptive restoration for underwater image quality degradation

In this paper, we present one simplify underwater image restoration model combined with Total variation (TV) regularized Richardson-Lucy (RL) algorithm. Poor visibility in the sea and the variations in the illumination, viewpoints, etc., have been comprehensively taken into consideration for image restoration. An adaptive image restoration strategy by Improvement signal-to-noise ratio (ISNR) is then made full use of to undertake the underwater image restoration. A non-reference restored image quality evaluation criterion called relative gray mean grads (RGMG) is defined on the basis of other evaluation criterion called gray mean grads (GMG). 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 matching precision for the underwater images.