基于特征轮廓配准的多波束声纳与侧扫声纳数据融合

Yanling Hao, Qingnan Han
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引用次数: 3

摘要

提出了一种基于特征轮廓的同名特征点配准方法。通过分析多波束水深图的假灰度图像和侧扫声纳图像,采用CANNY算子提取等高线。然后选取满足约束条件的拐点作为特征点,用二次多项式算法对特征点进行处理,得到变形模型,实现两者之间的图像配准。最后对融合结果进行小波分解处理,并用交叉熵算法进行评价。数据仿真结果表明,所得结果是合理的,所提出的方法是可行的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data fusion of multi-beam sonar and side-scan sonar base on feature contour registration
This paper proposed a same-name feature point registration method based on feature contour. By analyzing the map of multi-beam water depth false-gray image and side-scan sonar image, and adopting CANNY operator to extract contour line. Then select the turning points which cater the constraints as the feature points, and deal the feature points with quadratic polynomial algorithm to obtain the deformation model to realize image registration between the two. Finally, process the fusion result by wavelet decomposition and evaluate it by cross entropy algorithm. Data simulation shows that the result is reasonable and the method proposed in this paper is practicable.
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