Research on Underwater Image Enhancement Algorithm Based on Physical Model

In this research work, an improved underwater image enhancement algorithm is presented that is based on physical modeling techniques. It aims to improve the quality of underwater images by addressing color differences and blur. The proposed algorithm performs better than other advanced and classical underwater image enhancement methods. The method is composed of a two-step process. First, a coarse transfer map is estimated, which optimizes the contrast and minimizes the loss of information during the image mapping process. Dark channel preprocessing and guided filter refinement are used to improve transmission map accuracy. Second, the occluded light is estimated by considering the differential attenuation of the red, green, and blue light underwater, thereby mitigating the color differences caused by the attenuation effects and solving the blur problem based on the image models. In addition, the gray world method is used for color correction, resulting in a deblurred and color corrected underwater image. In particular, it addresses color differences and blurriness in underwater imagery caused by light attenuation at different wavelengths, visible light diffusion, and diffusion from plankton and debris. The ability to significantly improve the quality of underwater images is the significance of this enhanced algorithm. This enhancement gives researchers a more apparent and reliable basis for understanding and analyzing underwater environments and phenomena. It has far-reaching implications for various fields, including marine biology, underwater archaeology, and oceanography, as it improves the accuracy of research and applications in these domains.