A Comprehensive Analysis of Underwater Image Processing based on Deep Learning Techniques

Underwater image processing has been an active research topic over the past few years as interest in marine observation and the use of ocean resources has increased. Different from conventional images, marine ecosystems are frequently subjected to challenging conditions such as underwater turbulence, low contrast, and high colour distortion as a result of the light's non-uniform attenuation as it passes through the water. To overcome these challenges, a good amount of work in conventional and deep learning based underwater image processing has been published over a period of time. Deep learning has demonstrated excellent performance improvement than the conventional approaches on the challenging vision tasks. In this survey, important underwater image processing methods using deep learning have been discussed. The major underwater metrics, common datasets, and challenges are also presented.