Next Article in Journal
Survey of 8 UAV Set-Covering Algorithms for Terrain Photogrammetry
Previous Article in Journal
A Practical Methodology for Generating High-Resolution 3D Models of Open-Pit Slopes Using UAVs: Flight Path Planning and Optimization
Article

Super Resolution by Deep Learning Improves Boulder Detection in Side Scan Sonar Backscatter Mosaics

Leibniz Institute for Baltic Sea Research Warnemünde, Seestrasse 15, 18119 Warnemünde, Germany
Remote Sens. 2020, 12(14), 2284; https://doi.org/10.3390/rs12142284
Received: 5 June 2020 / Revised: 3 July 2020 / Accepted: 14 July 2020 / Published: 16 July 2020
In marine habitat mapping, a demand exists for high-resolution maps of the seafloor both for marine spatial planning and research. One topic of interest is the detection of boulders in side scan sonar backscatter mosaics of continental shelf seas. Boulders are oftentimes numerous, but encompass few pixels in backscatter mosaics. Therefore, both their automatic and manual detection is difficult. In this study, located in the German Baltic Sea, the use of super resolution by deep learning to improve the manual and automatic detection of boulders in backscatter mosaics is explored. It is found that upscaling of mosaics by a factor of 2 to 0.25 m or 0.125 m resolution increases the performance of small boulder detection and boulder density grids. Upscaling mosaics with 1.0 m pixel resolution by a factor of 4 improved performance, but the results are not sufficient for practical application. It is suggested that mosaics of 0.5 m resolution can be used to create boulder density grids in the Baltic Sea in line with current standards following upscaling. View Full-Text
Keywords: habitat mapping; hydroacoustics; boulder detection; neural network; Baltic Sea; deep learning; backscatter mosaic habitat mapping; hydroacoustics; boulder detection; neural network; Baltic Sea; deep learning; backscatter mosaic
Show Figures

Graphical abstract

MDPI and ACS Style

Feldens, P. Super Resolution by Deep Learning Improves Boulder Detection in Side Scan Sonar Backscatter Mosaics. Remote Sens. 2020, 12, 2284. https://doi.org/10.3390/rs12142284

AMA Style

Feldens P. Super Resolution by Deep Learning Improves Boulder Detection in Side Scan Sonar Backscatter Mosaics. Remote Sensing. 2020; 12(14):2284. https://doi.org/10.3390/rs12142284

Chicago/Turabian Style

Feldens, Peter. 2020. "Super Resolution by Deep Learning Improves Boulder Detection in Side Scan Sonar Backscatter Mosaics" Remote Sensing 12, no. 14: 2284. https://doi.org/10.3390/rs12142284

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 Access Map by Country/Region

1
Back to TopTop