Undersea Buried Pipeline Reconstruction Based on the Level Set and Inverse Multiquadric Regularization Method

被引:0
作者
Wenjing Shang
Wei Xue
Yidong Xu
Sergey B. Makarov
Yingsong Li
机构
[1] Harbin Engineering University,College of Information and Communication Engineering
[2] Ministry of Industry and Information Technology,Key Laboratory of Advanced Marine Communication and Information Technology
[3] Yantai Research Institute and Graduate School of Harbin Engineering University,Institute of Physics, Nanotechnology and Telecommunications, Higher School of Applied Physics and Space Technologies
[4] Peter the Great St. Petersburg Polytechnic University,undefined
来源
Journal of Ocean University of China | 2022年 / 21卷
关键词
inverse problems; level set function; inverse multiquadric regularization method; buried pipeline;
D O I
暂无
中图分类号
学科分类号
摘要
The electric inversion technique reconstructs the subsurface medium distribution from acquired data. On the basis of electric inversion, objects buried under the earth or seabed, such as pipelines and unexploded ordnance, are detected and located in a contactless manner. However, the process of accurately reconstructing the shape of the target object is challenging because electric inversion is a nonlinear and ill-posed problem. In this work, we present an inverse multiquadric (IMQ) regularization method based on the level set function for reconstructing buried pipelines. In the case of locating underwater objects, the unknown inversion area is split into two parts, the background and the pipeline with known conductivity. The geometry of the pipeline is represented based on the level set function for achieving a noiseless inversion image. To obtain a binary image, the IMQ is used as the regularization term, which ‘pushes’ the level set function away from 0. We also provide an appropriate method to select the bandwidth and regularization parameters for the IMQ regularization term, resulting in reconstructed images with sharp edges. The simulation results and analysis show that the proposed method performs better than classical inversion methods.
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页码:101 / 112
页数:11
相关论文
共 148 条
[1]  
Adler A(2006)Uses and abuses of eidors: An extensible software base for EIT Physiological Measurement 27 S25-650
[2]  
Lionheart W R(2011)Parametric level set methods for inverse problems SIAM Journal on Imaging Sciences 4 618-3446
[3]  
Aghasi A(2013)Resolution and stability analysis in full-aperture, linearized conductivity and wave imaging Proceedings of the American Mathematical Society 141 3431-2553
[4]  
Kilmer M(2011)Dart: A practical reconstruction algorithm for discrete tomography IEEE Transactions on Image Processing 20 2542-5054
[5]  
Miller E L(2017)Model based object localization and shape estimation using electric sense on underwater robots IFAC—PapersOnLine 50 5047-587
[6]  
Ammari H(2012)A primal-dual interior-point framework for using the L1 or L2 norm on the data and regularization terms of inverse problems Inverse Problems 28 095011-108
[7]  
Garnier J(2002)Generation of anisotropic-smoothness regularization filters for EIT IEEE Transactions on Medical Imaging 21 579-145
[8]  
Sølna K(2003)Electrical impedance tomography (EIT): A review Journal of Medical Engineering and Technology 27 97-300
[9]  
Batenburg K J(2011)A first-order primal-dual algorithm for convex problems with applications to imaging Journal of Mathematical Imaging and Vision 40 120-282
[10]  
Sijbers J(2019)An accurate localization method for subsea pipelines by using external magnetic fields Measurement 147 106803-1586