Optical Imaging and Image Restoration Techniques for Deep Ocean Mapping: A Comprehensive Survey

Abstract

Visual systems are receiving increasing attention in underwater applications. While the photogrammetric and computer vision literature so far has largely targeted shallow water applications, recently also deep sea mapping research has come into focus. The majority of the seafloor, and of Earth’s surface, is located in the deep ocean below 200 m depth, and is still largely uncharted. Here, on top of general image quality degradation caused by water absorption and scattering, additional artificial illumination of the survey areas is mandatory that otherwise reside in permanent darkness as no sunlight reaches so deep. This creates unintended non-uniform lighting patterns in the images and non-isotropic scattering effects close to the camera. If not compensated properly, such effects dominate seafloor mosaics and can obscure the actual seafloor structures. Moreover, cameras must be protected from the high water pressure, e.g. by housings with thick glass ports, which can lead to refractive distortions in images. Additionally, no satellite navigation is available to support localization. All these issues render deep sea visual mapping a challenging task and most of the developed methods and strategies cannot be directly transferred to the seafloor in several kilometers depth. In this survey we provide a state of the art review of deep ocean mapping, starting from existing systems and challenges, discussing shallow and deep water models and corresponding solutions. Finally, we identify open issues for future lines of research.

On the Adaptation of an AUV into a Dedicated Platform for Close Range Imaging Survey Missions

“…where B 0 is the unconstrained allocation matrix (11), B is initialized with B 0 and updated according to the thrusters' availability, c is initialized with zeros and updated according to the thrusters' saturation, and I 3 is an identity matrix. is a small regularization parameter defined to avoid singularity in the RPI expression when B does not possess full rank and W is a weighting matrix.…”

“…These features make AUVs an excellent candidate platform for underwater visual survey missions [2,10]. Consequently, dedicated imaging and lighting systems have been developed [11][12][13]. Methods for improving the capabilities of AUVs' during autonomous visual mapping and survey missions were also recently introduced [14,15], and new concepts of low cost AUVs for close-to-seabed and high-resolution imaging in shallow water have been proposed [16,17].…”

Virtually Throwing Benchmarks Into the Ocean for Deep Sea Photogrammetry and Image Processing Evaluation

“…It is regularly applied in photometric stereo approaches in participating media. See (Song et al, 2022) for a recent survey on the different models.…”

“…Simultaneously obtaining a deep sea scene and its corresponding GT appearance without water or lighting effects is practically impossible. The lack of proper deep sea vision datasets with GT is impairing the development of corresponding vision methods (Song et al, 2022).…”

Investigation of the Challenges of Underwater-Visual-Monocular-Slam

“…However, the accuracy of monocular vSLAM methods can be significantly impacted by environmental conditions, particularly low visibility and extreme lighting scenarios, which are common in underwater environments. To address this challenge, various image enhancement techniques have been proposed to improve the quality of the input images and thereby enhance the performance of monocular vSLAM methods (Song et al, 2022). These techniques comprise rather heuristic, physically-basedly-based as well as machine learning-based approaches, such as Generative Adversarial Networks (GANs).…”