Underwater Image Restoration

Underwater image restoration aims to improve the quality of underwater images degraded by factors like color distortion, low contrast, and scattering. Current research focuses on developing sophisticated deep learning models, often employing multi-scale and multi-resolution architectures, variational methods, and diffusion priors, to effectively remove these artifacts and enhance image details. These advancements are crucial for improving the performance of underwater autonomous systems, enhancing underwater surveys and exploration, and facilitating various applications in marine science and engineering. The field is also actively exploring unsupervised and semi-supervised learning techniques to address the scarcity of labeled training data.