Underwater Image Enhancement Using Convolutional Neural Network and the MultiUnet Model

This research introduces a novel approach to enhance underwater images combining Convolutional Neural Networks (CNN) for accurate classification and U-Net for in-depth feature extraction. The integrated model addresses the unique challenges posed by underwater environments, such as poor visibility and color distortion, and results in a noticeable improvement in things detection precision. The entire system offers a strong foundation for advancing the field of underwater image processing and has enormous potential applications in underwater robotics, environmental monitoring, and marine biology.