Underwater Single Image Dehazing Using the Color Space Dimensionality Reduction Prior

Underwater images suffer from low visibility and contrast caused by absorption and scattering, which leads to haze and some further limitations. The existing underwater single image dehazing methods cannot achieve a balance between the performance and computational complexity, and are difficult to produce satisfactory results in the regions with large distance. To overcome these problems, we propose a new underwater single image dehazing method, which includes an improved background light estimation based on the quad-tree subdivision iteration algorithm, and a novel transmission estimation method. For the background light estimation, we introduce a robust score for each region of the image, which can evaluate the region from both smoothness and color. For the transmission estimation, we propose the color space dimensionality reduction prior (CSDRP), which allows conversing an image from the three-dimensional RGB color space to a 2D color space, namely the UV color space. In the UV color space, by clustering the pixels into mounts of haze-lines and carefully setting the haze-free boundary, the transmission map can be figured out and used to produce an excellent dehazed image. Experimental results show that our method has competitive effects compared with mainstream underwater single image dehazing methods.