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IOP Publishing, IOP Conference Series: Earth and Environmental Science, 1(660), p. 012083, 2021

DOI: 10.1088/1755-1315/660/1/012083

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Application of update lifting morphological wavelet and non-negative matrix factorization for wheeled and tracked vehicles classification

Journal article published in 2021 by Kai Ding, Kai Du, Xiaogang Qi, Yuelin Xu, Junqi Cui
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Abstract This paper presents an available scheme based on update lifting morphological wavelet (ULMW) and Non-negative matrix factorization (NMF) for wheeled and tracked vehicles classification. The ULWM algorithm which utilizes the update operator, means the morphological filter to replace the linear filter can preserve the impulsive shape details in seismic signal. Meanwhile the NMF method can reduce the computation cost. The traditional linear wavelet analysis and statistical analysis are compared with the presented scheme. Experimental results demonstrate that the presented scheme achieves a promising performance on extracting impulsive features of seismic signal and recognizing ground moving target.