Improving GPR Imaging of the Buried Water Utility Infrastructure by Integrating the Multidimensional Nonlinear Data Decomposition Technique into the Edge Detection

Although ground-penetrating radar (GPR) is effective to detect shallow-buried objects, it still needs more effort for the application to investigate a buried water utility infrastructure. Edge detection is a well-known image processing technique that may improve the resolution of GPR images. In this...

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Autores principales:	Chih-Sung Chen, Yih Jeng
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	GPR edge detection near-surface imaging spectrogram multidimensional EMD water management Hydraulic engineering TC1-978 Water supply for domestic and industrial purposes TD201-500
Acceso en línea:	https://doaj.org/article/ad10ca4e3bd64447958ad3cf77e16423
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spelling	oai:doaj.org-article:ad10ca4e3bd64447958ad3cf77e164232021-11-11T19:58:33ZImproving GPR Imaging of the Buried Water Utility Infrastructure by Integrating the Multidimensional Nonlinear Data Decomposition Technique into the Edge Detection10.3390/w132131482073-4441https://doaj.org/article/ad10ca4e3bd64447958ad3cf77e164232021-11-01T00:00:00Zhttps://www.mdpi.com/2073-4441/13/21/3148https://doaj.org/toc/2073-4441Although ground-penetrating radar (GPR) is effective to detect shallow-buried objects, it still needs more effort for the application to investigate a buried water utility infrastructure. Edge detection is a well-known image processing technique that may improve the resolution of GPR images. In this study, we briefly review the theory of edge detection and discuss several popular edge detectors as examples, and then apply an enhanced edge detecting method to GPR data processing. This method integrates the multidimensional ensemble empirical mode decomposition (MDEEMD) algorithm into standard edge detecting filters. MDEEMD is implemented mainly for data reconstruction to increase the signal-to-noise ratio before edge detecting. A quantitative marginal spectrum analysis is employed to support the data reconstruction and facilitate the final data interpretation. The results of the numerical model study followed by a field example suggest that the MDEEMD edge detector is a competent method for processing and interpreting GPR data of a buried hot spring well, which cannot be efficiently handled by conventional techniques. Moreover, the proposed method should be readily considered a vital tool for processing other kinds of buried water utility infrastructures.Chih-Sung ChenYih JengMDPI AGarticleGPRedge detectionnear-surface imagingspectrogrammultidimensional EMDwater managementHydraulic engineeringTC1-978Water supply for domestic and industrial purposesTD201-500ENWater, Vol 13, Iss 3148, p 3148 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	GPR edge detection near-surface imaging spectrogram multidimensional EMD water management Hydraulic engineering TC1-978 Water supply for domestic and industrial purposes TD201-500
spellingShingle	GPR edge detection near-surface imaging spectrogram multidimensional EMD water management Hydraulic engineering TC1-978 Water supply for domestic and industrial purposes TD201-500 Chih-Sung Chen Yih Jeng Improving GPR Imaging of the Buried Water Utility Infrastructure by Integrating the Multidimensional Nonlinear Data Decomposition Technique into the Edge Detection
description	Although ground-penetrating radar (GPR) is effective to detect shallow-buried objects, it still needs more effort for the application to investigate a buried water utility infrastructure. Edge detection is a well-known image processing technique that may improve the resolution of GPR images. In this study, we briefly review the theory of edge detection and discuss several popular edge detectors as examples, and then apply an enhanced edge detecting method to GPR data processing. This method integrates the multidimensional ensemble empirical mode decomposition (MDEEMD) algorithm into standard edge detecting filters. MDEEMD is implemented mainly for data reconstruction to increase the signal-to-noise ratio before edge detecting. A quantitative marginal spectrum analysis is employed to support the data reconstruction and facilitate the final data interpretation. The results of the numerical model study followed by a field example suggest that the MDEEMD edge detector is a competent method for processing and interpreting GPR data of a buried hot spring well, which cannot be efficiently handled by conventional techniques. Moreover, the proposed method should be readily considered a vital tool for processing other kinds of buried water utility infrastructures.
format	article
author	Chih-Sung Chen Yih Jeng
author_facet	Chih-Sung Chen Yih Jeng
author_sort	Chih-Sung Chen
title	Improving GPR Imaging of the Buried Water Utility Infrastructure by Integrating the Multidimensional Nonlinear Data Decomposition Technique into the Edge Detection
title_short	Improving GPR Imaging of the Buried Water Utility Infrastructure by Integrating the Multidimensional Nonlinear Data Decomposition Technique into the Edge Detection
title_full	Improving GPR Imaging of the Buried Water Utility Infrastructure by Integrating the Multidimensional Nonlinear Data Decomposition Technique into the Edge Detection
title_fullStr	Improving GPR Imaging of the Buried Water Utility Infrastructure by Integrating the Multidimensional Nonlinear Data Decomposition Technique into the Edge Detection
title_full_unstemmed	Improving GPR Imaging of the Buried Water Utility Infrastructure by Integrating the Multidimensional Nonlinear Data Decomposition Technique into the Edge Detection
title_sort	improving gpr imaging of the buried water utility infrastructure by integrating the multidimensional nonlinear data decomposition technique into the edge detection
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/ad10ca4e3bd64447958ad3cf77e16423
work_keys_str_mv	AT chihsungchen improvinggprimagingoftheburiedwaterutilityinfrastructurebyintegratingthemultidimensionalnonlineardatadecompositiontechniqueintotheedgedetection AT yihjeng improvinggprimagingoftheburiedwaterutilityinfrastructurebyintegratingthemultidimensionalnonlineardatadecompositiontechniqueintotheedgedetection
_version_	1718431368860401664

Improving GPR Imaging of the Buried Water Utility Infrastructure by Integrating the Multidimensional Nonlinear Data Decomposition Technique into the Edge Detection

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