Underwater Image Classification and Enhancement using AI Techniques: A Review

The classification and enhancement of underwater images are significant applications of artificial intelligence in marine science, environmental monitoring, and underwater robotics, which serve to help interpret and analyze images in water environments. Images taken underwater may be distorted, have low contrast, light scattering and missing details, all of which will affect classification accuracy. It reviews the traditional image processing methods along with AI techniques, such as Convolutional Neural Networks (CNNs), Generative Adversarial Networks (GANs), and Transformer models, to enhance image quality and classification accuracy. It also addresses issues with datasets, identification, evaluation metrics, challenges, and future research directions. The review underscores the importance of the development of powerful, efficient and task-oriented AI models that can reliably analyze underwater images in various environments.