Underwater image restoration based on modified color-line model

Underwater images suffer from haze, color distortion, and low contrast due to the absorption and scattering of transmitted light. A systematic approach including accurate background light (BL) estimation and transmission (TM) estimation is proposed based on color-line model for underwater images restoration. The estimation of BL candidate region is improved by combining quadtree subdivision and minimum unary gray entropy evaluation, to realize a high-quality restoration and improve accuracy of TM estimation with color-line model. Given incomplete intersection of color lines with BL, a convex optimization function is proposed to improve accuracy of TM estimation. On the basis of restorations with BL and TM estimations, pixel distribution stretching and Unsharp Masking are employed to correct color and enhance edge information for better performance of vision. Comprehensive evaluations illustrate that the proposed method could efficiently restore underwater images with visibility improvement, natural color correction, and contrast enhancement.