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引用次数: 3

摘要

在几乎任何在海底上或海底下进行的水下作业中,都有必要了解淤泥和沉积物下面的海底构成。声纳是一种广泛用于水下探测和海底分类的声学系统。本文讨论了基于声学海底自动识别系统的海底自动分割分类问题,提出了一种基于标准小波变换的分割合并算法。在真实原型数据上的实验结果表明了该算法的鲁棒性和有效性。
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Wavelet-based acoustic seabed discrimination system
In almost any underwater operation that takes place on or under the seafloor, it is necessary to have an understanding of the makeup of the seabed below the silt and sediment. Sonar is an acoustic system extensively used for underwater inspection as well as seabed classification. In this paper, the problem of automatic segmentation and classification of seafloor using automatic acoustic seabed discrimination systems is discussed and a new split and merge algorithm based on the concept of standard wavelet transform is presented. Experimental results on true prototype data indicate the robustness and effectiveness of the proposed algorithm.
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