Improving the Total Variation De-noising algorithm in GPR noise reduction
پذیرفته شده برای ارائه شفاهی ، صفحه 60-63 (4)
اصل مقاله (472.49 K)
عنوان دوره: نوزدهمین کنفرانس ژئوفیزیک ایران
کد مقاله : 1455-NIGS
نویسندگان
1زمین شناسی، دانشگاه پیام نور واحد پرند ، استان تهران، ایران
2ژئوفیزیک، موسسه ژئوفیزیک دانشگاه تهران
3هیئت علمی دانشگاه تحصیلات تکمیلی کرمان
4Tehran University
چکیده
The existence of coherent and incoherent (random) noises in the Ground Penetrating Radar (GPR) signals which utilizes the high-frequency electromagnetic waves, is inevitable; therefore de-noising of the GPR data before performing any further analysis, is of great importance to increase the efficiency of the interpretations. In this paper, we apply the Total Variation De-noising (TVD) on the synthetic GPR data. The results point to the fact that the TVD method is effective in reducing the noise; however, because of the visibility of the staircase artifacts using TVD method, the GPR data is first transferred to the Empirical Mode Decomposition (EMD) framework and then the TVD method is applied on it. In final, the noise reduction using TVD is compared in time and EMD domains. The comparison of the outputs represents that the TVD-EMD algorithm preserves the event shapes, the signal forms and improves the continuity in the sections.
کلیدواژه ها
De-noising؛ Ground penetrating radar (GPR)؛ Empirical Mode Decomposition (EMD)؛ Total Variation De-noising (TVD)
Title
Improving the Total Variation De-noising algorithm in GPR noise reduction
Authors
asghar azadi, sadegh moghadam, Alireza Goudarzi, Behrooz Oskooi
Abstract
The existence of coherent and incoherent (random) noises in the Ground Penetrating Radar (GPR) signals which utilizes the high-frequency electromagnetic waves, is inevitable; therefore de-noising of the GPR data before performing any further analysis, is of great importance to increase the efficiency of the interpretations. In this paper, we apply the Total Variation De-noising (TVD) on the synthetic GPR data. The results point to the fact that the TVD method is effective in reducing the noise; however, because of the visibility of the staircase artifacts using TVD method, the GPR data is first transferred to the Empirical Mode Decomposition (EMD) framework and then the TVD method is applied on it. In final, the noise reduction using TVD is compared in time and EMD domains. The comparison of the outputs represents that the TVD-EMD algorithm preserves the event shapes, the signal forms and improves the continuity in the sections.
Keywords
De-noising, Ground penetrating radar (GPR), Empirical Mode Decomposition (EMD), Total Variation De-noising (TVD)