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Article

GPR Clutter Reflection Noise-Filtering through Singular Value Decomposition in the Bidimensional Spectral Domain

1
Instituto de Ciências da Terra, ICT, Universidade de Évora, Apartado 94, 7002-554 Évora, Portugal
2
Departamento de Física, Escola de Ciências e Tecnologia, Universidade de Évora, Apartado 94, 7002-554 Évora, Portugal
3
Earth Remote Sensing Laboratory, EaRSLab, Universidade de Évora, Apartado 94, 7002-554 Évora, Portugal
4
Instituto Andaluz de Geofísica, Campus Universitario de Cartuja, Universidad de Granada, 18071 Granada, Spain
*
Author to whom correspondence should be addressed.
Academic Editors: Yuri Álvarez López and María García Fernández
Remote Sens. 2021, 13(10), 2005; https://doi.org/10.3390/rs13102005
Received: 4 May 2021 / Accepted: 15 May 2021 / Published: 20 May 2021
(This article belongs to the Special Issue Advanced Techniques for Ground Penetrating Radar Imaging)
Usually, in ground-penetrating radar (GPR) datasets, the user defines the limits between the useful signal and the noise through standard filtering to isolate the effective signal as much as possible. However, there are true reflections that mask the coherent reflectors that can be considered noise. In archaeological sites these clutter reflections are caused by scattering with origin in subsurface elements (e.g., isolated masonry, ceramic objects, and archaeological collapses). Its elimination is difficult because the wavelet parameters similar to coherent reflections and there is a risk of creating artefacts. In this study, a procedure to filter the clutter reflection noise (CRN) from GPR datasets is presented. The CRN filter is a singular value decomposition-based method (SVD), applied in the 2D spectral domain. This CRN filtering was tested in a dataset obtained from a controlled laboratory environment, to establish a mathematical control of this algorithm. Additionally, it has been applied in a 3D-GPR dataset acquired in the Roman villa of Horta da Torre (Fronteira, Portugal), which is an uncontrolled environment. The results show an increase in the quality of archaeological GPR planimetry that was verified via archaeological excavation. View Full-Text
Keywords: applied geophysics; digital signal processing; enhancement of 3D-GPR datasets; clutter noise removal; spectral filtering applied geophysics; digital signal processing; enhancement of 3D-GPR datasets; clutter noise removal; spectral filtering
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MDPI and ACS Style

Oliveira, R.J.; Caldeira, B.; Teixidó, T.; Borges, J.F. GPR Clutter Reflection Noise-Filtering through Singular Value Decomposition in the Bidimensional Spectral Domain. Remote Sens. 2021, 13, 2005. https://doi.org/10.3390/rs13102005

AMA Style

Oliveira RJ, Caldeira B, Teixidó T, Borges JF. GPR Clutter Reflection Noise-Filtering through Singular Value Decomposition in the Bidimensional Spectral Domain. Remote Sensing. 2021; 13(10):2005. https://doi.org/10.3390/rs13102005

Chicago/Turabian Style

Oliveira, Rui J., Bento Caldeira, Teresa Teixidó, and José F. Borges 2021. "GPR Clutter Reflection Noise-Filtering through Singular Value Decomposition in the Bidimensional Spectral Domain" Remote Sensing 13, no. 10: 2005. https://doi.org/10.3390/rs13102005

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