Underwater Color

Underwater color correction aims to restore the true colors of objects captured in underwater images, which are often distorted by water's absorption and scattering of light. Current research focuses on developing computationally efficient deep learning models, often employing encoder-decoder architectures and convolutional neural networks, to address the color distortions in real-time, particularly for applications in autonomous underwater vehicles. These advancements are crucial for improving the accuracy and reliability of underwater vision systems used in various fields, including marine biology, environmental monitoring, and underwater robotics. The development of faster and more accurate algorithms is driving progress in this area.