An Advanced Visibility Restoration Technique for Underwater Images

Images captured in underwater (UW) are often disturbed with several kind of degradation such as low visibility, non-uniform color cast, haze, and blurriness. To date, most UW image restoration methods have ignored the effects of sensor blur and noise. Therefore, in this paper, we propose a novel three stage algorithm for visibility recovery in UW images by considering both sensor blur and noise. In the first stage, blind deconvolution is used for the estimation of an unknown point spread function (PSF). In the second stage, a new prior called weighted median channel prior (WMCP) is used for the estimation of scene depth and background light. In the third stage, a color balancing (CB) module is adopted to minimize the effect of non-uniform color cast. Experimental results manifest that the proposed algorithm is effective and has the character of visibility improvement, and color correction than previous state-of-the-art methods.