Study on Underwater Image Enhancement Techniques and Their Evaluation Metrics

Underwater imaging poses unique challenges due to the adverse optical properties of water, leading to significant degradation in image quality. In this research paper, present a comprehensive study of underwater image enhancement techniques aimed at mitigating the detrimental effects of the underwater environment. We analyze and compare various traditional and state-of-the-art machine learning-based algorithms, discussing their strengths, limitations, and performance in different underwater imaging scenarios. Additionally, we explore evaluation metrics commonly used to assess the quality of enhanced underwater images and identify the remaining challenges in the field. This study serves as a valuable resource for researchers and practitioners interested in developing effective underwater image enhancement methods and advancing the field.