一种结合SLAM和弹性匹配的侧扫声纳自动拼接混合配准方法

Loic Bernicola, D. Guériot, J. Le Caillec
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引用次数: 4

摘要

本文介绍了一种混合配准方法,用于侧扫声纳图像的拼接。由于调查过程中特定的采集程序,标准SLAM技术可能不够强大,无法全面考虑完整的调查和正确的传感器轨迹,以便正确地参考所有这些图像中的每个像素。iSAM算法使用了真实的侧面扫描图像,并显示出基于地标提取和配对产生校正传感器轨迹的有趣功能,从而允许相关的粗图像配准。然后,这些轨迹将指导一个块匹配程序,该程序将通过精细匹配声纳图像的相关区域来细化这些轨迹。
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A hybrid registration approach combining SLAM and elastic matching for automatic side-scan sonar mosaic
This paper introduces a hybrid registration approach to build mosaics from side-scan sonar images. Due to specific acquisition procedure during surveys, standard SLAM techniques may not be robust enough to globally take into account a complete survey and correct sensor trajectories in order to properly georeference every pixel from all these images. iSAM algorithm has been fed with real side-scan images and shows interesting capabilities to produce corrected sensor trajectories allowing relevant coarse image registration, based on landmarks extraction and pairing. These trajectories will then guide a block-matching procedure that will refine these trajectories by finely matching only sonar images relevant areas.
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