侧扫声纳图像的几何校正

Tal Sheffer, H. Guterman
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引用次数: 2

摘要

水下环境使目标探测任务变得困难。侧扫声纳(SSS)已被发现适用于海底扫描任务,但从SSS获得的声纳图像往往存在较大的噪声和几何畸变,这改变了对海底物体的纹理、大小和形状的理解。因此,为了识别海底物体,通过减少变形来重建实际形状是至关重要的。本文提出了一种利用强度归一化、倾斜距离校正、偏航和俯仰校正、速度和位置校正等方法对声纳图像图进行校正和重建的方法。这是利用自主水下航行器传感器获得的导航和惯性数据完成的。
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Geometrical Correction of Side-scan Sonar Images
The underwater environment makes object-detection missions difficult. Side-scan Sonar (SSS) has been found to be suitable for seabed scanning missions, however the sonar images acquired from SSS often suffer from considerable noise and geometrical distortion, which changes the understanding of the texture, size, and shape of seabed objects. In order to identify seabed objects, it is thus vital to reconstruct the actual shape by reducing distortion. This paper proposes a process for correcting and reconstructing the sonar image map that utilizes intensity normalization, slant range correction, yaw and pitch correction, and speed and location correction. This is done using navigation and inertial data acquired by the autonomous underwater vehicle sensors.
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