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Computer vision techniques applied for reconstruction of seafloor 3D images from side scan and synthetic aperture sonars data
Abstract
The Side Scan Sonar and Synthetic Aperture Sonar are well known echo signal processing technologies that produce 2D images of the seafloor. Both systems combines a number of acoustic pings to form a high resolution image of seafloor. It was shown in numerous papers that 2D images acquired by such systems can be transformed into 3D models of seafloor surface by algorithmic approach using intensity information, contained in a grayscaled images.The paper presents the concept of processing the Side Scan Sonar and Synthetic Aperture Sonar records for detailed reconstruction of 3D seafloor using Shape from Shading techniques. Shape from Shading is one of the basic techniques used in computer vision for the objects reconstruction. The algorithms proposed in the paper use the assumed Lambert model of backscattering strength dependence on incident angle and utilize additionally the information from shadow areas for solving obtained set of equations. The idea was verified by simulation study. The obtained results of 3D shape reconstruction are presented and the performance of the algorithms is discussed.
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Details
- Category:
- Conference activity
- Type:
- publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
- Title of issue:
- ECUA 2008 : Proceedings of the 9th European Conference on Underwater Acoustics Paris, France 29 June - 4 July, 2008 Vol. 2 strony 465 - 468
- Language:
- English
- Publication year:
- 2008
- Bibliographic description:
- Bikonis K., Stepnowski A., Moszyński M.: Computer vision techniques applied for reconstruction of seafloor 3D images from side scan and synthetic aperture sonars data // ECUA 2008 : Proceedings of the 9th European Conference on Underwater Acoustics Paris, France 29 June - 4 July, 2008 Vol. 2/ ed. ed. M. E. Zakharia. Paris: French Society of Acoustics, 2008, s.465-468
- DOI:
- Digital Object Identifier (open in new tab) 10.1121/1.2935303
- Verified by:
- Gdańsk University of Technology
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