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To obtain the high-resolution seabed topography and overcome the limitations of existing topography reconstruction methods in requiring external bathymetric data and ignoring the effects of sediment variations and Side-Scan Sonar (SSS) image quality, this study proposes a method of reconstructing seabed topography from SSS images with a self-constraint condition. A reconstruction model is deduced by Lambert's law and the seabed scattering model. A bottom tracking method is put forward to get the along-track SSS towfish heights and the initial seabed topography in the SSS measuring area is established by combining the along-track towfish heights, towfish depths and tidal levels obtained from Global Navigation Satellite System (GNSS). The complete process of reconstructing seabed topography is given by taking the initial topography as self-constraint and the high-resolution seabed topography is finally obtained. Experiments verified the proposed method by the data measured in Zhujiang River, China. The standard deviation of less than 15 cm is achieved and the resolution of the reconstructed topography is about 60 times higher than that of the Digital Elevation Model (DEM) established by bathymetric data. The effects of noise, suspended bodies, refraction of wave in water column, sediment variation, the determination of iteration termination condition as well as the performance of the proposed method under these effects are discussed. Finally, the conclusions are drawn out according to the experiments and discussions. The proposed method provides a simple and efficient way to obtain high-resolution seabed topography from SSS images and is a supplement but not substitution for the existing bathymetric methods. [ABSTRACT FROM AUTHOR]

To obtain large-scale seabed surface image, this paper proposes a side-scan sonar (SSS) image mosaic method using couple feature points (CFPs) with constraint of track line positions. The SSS geocoded images are firstly used to form a coarsely mosaicked one and the overlapping areas between adjacent strip images can be determined based on geographic information. Inside the overlapping areas, the feature point (FP) detection and registration operation are adopted for both strips. According to the detected CFPs and track line positions, an adjustment model is established to accommodate complex local distortions as well as ensure the global stability. This proposed method effectively solves the problem of target ghosting or dislocation and no accumulated errors arise in the mosaicking process. Experimental results show that the finally mosaicked image correctly reflects the object distribution, which is meaningful for understanding and interpreting seabed topography. [ABSTRACT FROM AUTHOR]