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Proceedings Paper

Model based image restoration for underwater images
Author(s): Thomas Stephan; Peter Frühberger; Stefan Werling; Michael Heizmann
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Paper Abstract

The inspection of offshore parks, dam walls and other infrastructure under water is expensive and time consuming, because such constructions must be inspected manually by divers. Underwater buildings have to be examined visually to find small cracks, spallings or other deficiencies. Automation of underwater inspection depends on established water-proved imaging systems. Most underwater imaging systems are based on acoustic sensors (sonar). The disadvantage of such an acoustic system is the loss of the complete visual impression. All information embedded in texture and surface reflectance gets lost. Therefore acoustic sensors are mostly insufficient for these kind of visual inspection tasks. Imaging systems based on optical sensors feature an enormous potential for underwater applications. The bandwidth from visual imaging systems reach from inspection of underwater buildings via marine biological applications through to exploration of the seafloor. The reason for the lack of established optical systems for underwater inspection tasks lies in technical difficulties of underwater image acquisition and processing. Lightening, highly degraded images make a computational postprocessing absolutely essential.

Paper Details

Date Published: 24 May 2013
PDF: 9 pages
Proc. SPIE 8791, Videometrics, Range Imaging, and Applications XII; and Automated Visual Inspection, 87911F (24 May 2013); doi: 10.1117/12.2021990
Show Author Affiliations
Thomas Stephan, Karlsruher Institut für Technologie (Germany)
Peter Frühberger, Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung (Germany)
Stefan Werling, Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung (Germany)
Michael Heizmann, Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung (Germany)


Published in SPIE Proceedings Vol. 8791:
Videometrics, Range Imaging, and Applications XII; and Automated Visual Inspection
Fabio Remondino; Jürgen Beyerer; Fernando Puente León; Mark R. Shortis, Editor(s)

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