Correcting Image Refraction: Towards Accurate Aerial Image-Based Bathymetry Mapping in Shallow Waters

Agrafiotis, Panagiotis; Karantzalos, Konstantinos; Georgopoulos, Andreas; Skarlatos, Dimitrios

doi:10.3390/rs12020322

Submit to this Journal Review for this Journal Edit a Special Issue

Article Menu

...

Open AccessArticle

Correcting Image Refraction: Towards Accurate Aerial Image-Based Bathymetry Mapping in Shallow Waters

Panagiotis Agrafiotis

^1,*

Konstantinos Karantzalos

Andreas Georgopoulos

² and

Dimitrios Skarlatos

Lab of Photogrammetric Vision, Civil Engineering and Geomatics Dept., Cyprus University of Technology, 2-8 Saripolou str., 3036 Limassol, Cyprus

Department of Topography, School of Rural and Surveying Engineering, National Technical University of Athens, Zografou Campus, 9 Heroon Polytechniou str., 15780 Athens, Greece

Author to whom correspondence should be addressed.

Remote Sens. 2020, 12(2), 322; https://doi.org/10.3390/rs12020322

Received: 19 November 2019 / Revised: 4 January 2020 / Accepted: 14 January 2020 / Published: 18 January 2020

View Full-Text Download PDF

Browse Figures

Citation Export

Abstract

Although aerial image-based bathymetric mapping can provide, unlike acoustic or LiDAR (Light Detection and Ranging) sensors, both water depth and visual information, water refraction poses significant challenges for accurate depth estimation. In order to tackle this challenge, we propose an image correction methodology, which first exploits recent machine learning procedures that recover depth from image-based dense point clouds and then corrects refraction on the original imaging dataset. This way, the structure from motion (SfM) and multi-view stereo (MVS) processing pipelines are executed on a refraction-free set of aerial datasets, resulting in highly accurate bathymetric maps. Performed experiments and validation were based on datasets acquired during optimal sea state conditions and derived from four different test-sites characterized by excellent sea bottom visibility and textured seabed. Results demonstrated the high potential of our approach, both in terms of bathymetric accuracy, as well as texture and orthoimage quality. View Full-Text

Keywords: bathymetry; UAV; aerial imagery; seabed mapping; coastal mapping; refraction correction; DSM; image correction; SfM; machine learning

▼ Show Figures

Graphical abstract

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Share and Cite

MDPI and ACS Style

Agrafiotis, P.; Karantzalos, K.; Georgopoulos, A.; Skarlatos, D. Correcting Image Refraction: Towards Accurate Aerial Image-Based Bathymetry Mapping in Shallow Waters. Remote Sens. 2020, 12, 322. https://doi.org/10.3390/rs12020322

AMA Style

Agrafiotis P, Karantzalos K, Georgopoulos A, Skarlatos D. Correcting Image Refraction: Towards Accurate Aerial Image-Based Bathymetry Mapping in Shallow Waters. Remote Sensing. 2020; 12(2):322. https://doi.org/10.3390/rs12020322

Chicago/Turabian Style

Agrafiotis, Panagiotis, Konstantinos Karantzalos, Andreas Georgopoulos, and Dimitrios Skarlatos. 2020. "Correcting Image Refraction: Towards Accurate Aerial Image-Based Bathymetry Mapping in Shallow Waters" Remote Sensing 12, no. 2: 322. https://doi.org/10.3390/rs12020322

Find Other Styles

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Metrics

Abstract views Pdf views Html views

Article Menu

Correcting Image Refraction: Towards Accurate Aerial Image-Based Bathymetry Mapping in Shallow Waters

Abstract

Share and Cite

Article Metrics

Article Access Statistics

Article Access Map by Country/Region

Further Information

Guidelines

MDPI Initiatives

Follow MDPI