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http://dx.doi.org/10.5574/KSOE.2016.30.3.214

Comparative Study of Sonar Image Processing for Underwater Navigation  

Shin, Young-Sik (Civil and Environmental Engineering, KAIST)
Cho, Younggun (Civil and Environmental Engineering, KAIST)
Lee, Yeongjun (Korea Research Institute Ship and Ocean engineering (KRISO))
Choi, Hyun-Taek (Korea Research Institute Ship and Ocean engineering (KRISO))
Kim, Ayoung (Civil and Environmental Engineering, KAIST)
Publication Information
Journal of Ocean Engineering and Technology / v.30, no.3, 2016 , pp. 214-220 More about this Journal
Abstract
Imaging sonars such as side-scanning sonar or forward-looking sonar are becoming fundamental sensors in the underwater robotics field. However, using sonar images for underwater perception presents many challenges. Sonar images are usually low resolution with inherent speckled noise. To overcome the limited sensor information for underwater perception, we investigated preprocessing methods for sonar images and feature detection methods for a nonlinear scale space. In this paper, we focus on a comparative analysis of (1) preprocessing for sonar images and (2) the feature detection performance in relation to the scale space composition.
Keywords
Imaging Sonar; Image preprocessing; Feature detection; Image Enhancement; Underwater Navigation;
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