Underwater Image Enhancement based on Optimal Contrast and Attenuation Difference

The quality of underwater images is often marred by noticeable color casts and blurring, resulting from complex phenomena such as differential light attenuation based on wavelength, veiling scattering, scattering plankton suspended particles in water. In this paper, we propose an effective image enhancement method called Optimal Contrast Attenuation Difference (OCAD) to tackle these issues. OCAD employs a two-step approach. First, it estimates coarse transmission map optimizing contrast minimizing information loss during mapping. This then refined using combination dark channel prior guided filter refining techniques improve its accuracy. Second, the considering red, green, blue underwater. estimated utilized partially mitigate cast caused effect, while also addressing blurring imaging model. To further enhance quality, introduce Gray World approach correct obtain deblurred color-corrected image. evaluate performance our proposed method, extensive experiments are conducted well-established datasets, including EUVP, UIEB, RUIE datasets. Comparative analysis against state-of-the-art classical methods reveals that algorithm significantly enhances outperforms other terms improvement.