GPR data noise attenuation on the curvelet transform
Bao Qian-Zong1, Li Qing-Chun1, and Chen Wen-Chao2
1. College of Geology Engineering and Geomatics, Chang’an University, Xi’an, 710054, China.
2. School of Electronics & Information Engineering, Xi’an Jiaotong University, Xi’an 710049, China.
Abstract Signal extraction is critical in GRP data processing and noise attenuation. When the target depth is shallow, its reflection echo signal will overlap with the background noise, affecting the detection of arrival time and localization of the target. Thus, we propose a noise attenuation method based on the curvelet transform. First, the original signal is transformed into the curvelet domain, and then the curvelet coefficients of the background noise are extracted according to the distribution features that differ from the effective signal. In the curvelet domain, the coarse-scale curvelet atom is isotropic. Hence, a two-dimensional directional filter is designed to estimate the high-energy background noise in the coarse-scale domain, and then, attenuate the background noise and highlight the effective signal. In this process, we also use a subscale threshold value of the curvelet domain to filter out random noise. Finally, we compare the proposed method with the average elimination and 2D continuous wavelet transform methods. The results show that the proposed method not only removes the background noise but also eliminates the coherent interference and random noise. The numerical simulation and the real data application suggest and verify the feasibility and effectiveness of the proposed method.
Signal extraction|background noise|curvelet transform|threshold value|noise attenuation
Cite this article:
BAO Qian-Zong,LI Qing-Chun,CHEN Wen-Chao. GPR data noise attenuation on the curvelet transform[J]. APPLIED GEOPHYSICS, 2014, 11(3): 301-310.
[1]
Candès, E.J. and Donoho, D. L., 2004, New tight frames of curvelets and optimal representations of objects with piecewise C 2 singularities: Communications on Pure and Applied Mathematics, 57 (2), 219-266.
[2]
Candès, E.J. and Donoho, D.L., 2005, Continuous curvelet transform: I. resolution of the wavefront set: Applied and Computational Harmonic Analysis, 19 (2), 162-197.
[3]
Candès, E.J. and Donoho, D.L., 2005, Continuous curvelet transform: II. discretization and frames: Applied and Computational Harmonic Analysis, 19, 198-222.
[4]
Candès, E.J., Demanet, L., Donoho, D.L., and Ying, L.X., 2006, Fast discrete curvelet transforms: SIAM Multiscale Model Simul., 5 (3), 861-899.
[5]
Carevic, D., 1999, Clutter reduction and target detection in ground-penetrating radar data using wavelets: Proceeding of the SPIE Conference on Detection and Remediation Technologies for Mines and Mine-like Targets IV, Florida, US, 973-978.
[6]
Chen, W. C., Shi, Z.S., Wang, W. B., and Gao, J. H., 2000, Suppressing the direct wave noise in GPR data using the 2D continue directional wavelets: China Journal of Radio Science (in Chinese), 15 (3), 352-357.
[7]
Chen, W. C., Wang, W., Gao, J. H., Xu, J., and Wang, W. B, 2012, GPR clutter noise separation by statistical independency promotion: Proceeding of the 14th International Conference on Ground Penetrating Radar (GPR), Shanghai, China, 367-370.
[8]
Davis, J. D., 2004, Ground penetrating radar (2nd edition): the Institution of Electrical Engineers.
[9]
Hennenfent, G. and Herrmann, F. J., 2006, Seismic denoising with nonuniformly sampled curvelets: Computing in Science and Engineering, 8 (3), 16-25.
[10]
Herrmann, F. J., Böniger, U., and Verschuur, D.J., 2007, Non-linear primary-multiple separation with directional curvelet frames: Geophysical Journal International, 170 (2), 781-799.
[11]
Herrmann, F. J. and Hennenfent, G., 2008, Non-parametric seismic data recovery with curvelet frames: Geophysical Journal International, 173 (1), 233-248.
[12]
Karlsen, B., Larsen, J., Sørensen, H. B. D., and Jakobsen, K.B., 2001, Comparison of PCA and ICA-based clutter reduction in GPR systems for anti-personal landmine detection: Proceedings of the 11th IEEE Signal Processing Workshop on Statistical Signal Processing, Singapore, 146-149.
[13]
Karlsen, B., Sørensen, H. B. D., Larsen, J., and Jakobsen, K.B., 2002, Independent component analysis for clutter reduction in Ground Penetrating Radar data: Proceeding of the SPIE on Detection and Remediation Technologies for Mines and Mine-like Targets VII, California, US, 378-389.
[14]
Khan, U. S. and Al-Nuaimy, W., 2010, Background removal from GPR data using Eigenvalues: Proceeding of the 13th Int. Conf. Ground Penetrating Radar (GPR), Lecce, Italy, 1-5.
[15]
Kovalenko, V., Yarovoy, A.G., and Ligthart, L.P., 2007, A novel clutter suppression algorithm for landmine detection with GPR: IEEE Transactions on Geoscience and Remote Sensing, 45 (11), 3740-3751.
[16]
Li, A., Jiang, Y. S., Zhang, A. X. and Wang, W. B., 2004, Suppressing the direct wave interference in GPR data using adaptive interference canceling: China Journal of Radio Science (in Chinese), 19 (2), 223-227.
[17]
Ma, J. W. and Plonka, G., 2007, Combined Curvelet Shrinkage and Nonlinear Anisotropic Diffusion: IEEE Transactions on Image Processing, 16 (9), 2198-2206.
[18]
Neelamani, R., Baumstein, A. I., Gillard, D.G., Hadidi, M., and Soroka, W., 2008, Coherent and random noise attenuation using the curvelet transform: The Leading Edge, 27(2), 240-248.
[19]
Potin, D., Duflos, E., and Vanheeghe, P., 2006, Landmines ground- penetrating radar signal enhancement by digital filtering: IEEE Transactions on Geoscience and Remote Sensing, 44(9), 2393-2406.
[20]
Solimene, R., Cuccaro, A., Dell’Aversano, A., Catapano, I., and Soldovieri, F., 2014, Ground Clutter Removal in GPR Surveys: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7(3), 792-798.
[21]
Starck, J. L., Murtagh, F., Candes, E. J. and Donoho, D.L., 2003, Gray and color image contrast enhancement by the curvelet transform: IEEE transactions on Image Processing, 12(6), 706-716.
[22]
Su, Y., Huang, C. L., and Lei, T. W., 2006, Ground Penetrating Radar Theory and Applications: China Science Press.
[23]
Van der, M. A., and Gutpa, I. J., 2000, A novel signal processing technique for clutter reduction in GPR measurements of small, shallow land mines: IEEE Transactions on Geoscience and Remote Sensing, 38(6), 2627-2637.
[24]
Wang, Z. J., Zeng, Z. F., Xue, J., and Liu, S. X., 2005, The application of KL transform to remove horizontal coherent noise in GPR record: Journal of Jiling University (Earth Science Edition) (in Chinese), 35 (Sup), 124-127.
[25]
Zeng, Z. F., Liu, S. X., Wang, Z. J., and Xue, J., 2006, Principles of Ground-Penetrating Radar Method and Applications: China Science Press.
[26]
Zeng, Z. F., Wu, F. S., Huang, L., Liu, F. S., and Sun, J. G., 2009, The adaptive chirplet transform and its application in GPR target detection: Applied Geophysics, 6(2), 92-200.
2014, Vol. 11 
