PFG – Journal of Photogrammetry Remote Sensing and Geoinformation Science · 2022 · 38 citations · 201 references
Natural SciencesOcean EngineeringOceanographyDeep-sea OceanographyPhysical OceanographyRemote SensingBathymetryPhotogrammetrySeafloor MappingSeafloor TopographyUnderwater PerceptionUnderwater SurveyDeep-sea MappingPhotogrammetry For Underwater SurveyScattering EffectsUnderwater Image RestorationUnderwater Imaging SystemsUnderwater Optical ImagingUnderwater PhotogrammetryUnderwater Surveying
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.
201
Kaiming He, Jian Sun, Xiaoou Tang · IEEE Transactions on Pattern Analysis and Machine Intelligence · 2012 · 5.4K citations
Edwin H. Land, John J. McCann · Journal of the Optical Society of America · 1971 · 4K citations
Medicine, Physiology, Vision Science +14
Adaptive histogram equalization and its variations
Stephen M. Pizer, E. Philip Amburn, John D. Austin et al. · Computer Vision Graphics and Image Processing · 1987 · 3.9K citations
DehazeNet: An End-to-End System for Single Image Haze Removal
Bolun Cai, Xiangmin Xu, Kui Jia et al. · IEEE Transactions on Image Processing · 2016 · 3.3K citations · Full text