ابراهیمی بردر، ا.، اسکویی، ب.، و گودرزی، ع.، 1398، ارتقاء کارایی نوفه زدایی TV و GSTV در فضاهای RADWT و DTRADWT، نشریه پژوهشهای ژئوفیزیک کاربردی، 5 (1)، 29-55.
اویسی موخر، م.،1386، بررسی ساختار شکستگی سراب قنبر در جنوب شهر کرمانشاه با استفاده از روش رادار، مجله ژئوفیزیک ایران، 1 (1)، 81-89.
محمدی ویژه، م.، 1387، برداشت، پردازش و تفسیر داد های رادار نفوذی به زمین در منطقه شاهرود و مقایسه آن با نتایج ژئوالکتریک در منطقه مزبور، پایاننامه کارشناسی ارشد، دانشکده مهندسی معدن، نفت و ژئوفیزیک، دانشگاه صنعتی شاهرود.
مزینانی، ا.، 1389، بررسی ضخامت آسفالت با استفاده از روش GPR، پایاننامه کارشناسی ارشد، دانشکده مهندسی معدن، نفت و ژئوفیزیک، دانشگاه صنعتی شاهرود.
کامکار روحانی، ا.، اسحاقی، ا.، و عرب امیری، ع.، ١٣٩١، پردازش و تفسیر دادههای رادار نفوذی به زمین به منظور شناسایی حفرههای زیرسطحی و بررسی لایهبندی، دانه بندی و برآورد میزان رس در رسوبات زیرسطحی کم عمق، مجله فیزیک زمین و فضا، 38 (4)، 173-155.
گودرزی، ع.، 1392، تضعیف امواج زمین غلت و نوفههای اتفاقی با استفاده از برخی تکنیکهای تجزیه و تحلیل چندگانه تفکیکپذیر، پایاننامه دکتری تخصصی، موسسه ژئوفیزیک، دانشگاه تهران.
گودرزی، ع.، و ملائی، ف.، 1397، افزایش توان تفکیک دادههای لرزهای با استفاده از تبدیل موجک گسسته مختلط، نشریه پژوهشهای ژئوفیزیک کاربردی، 4 (2)، 211-223.
قنبری، س.، و حفیظی، م.، 1395، کاربرد مدلسازی پیشرو و الگوریتم پردازشی مناسب در تعیین محل قنات به روش GPR، مجله ژئوفیزیک ایران، 10 (2)، 67-82.
خداقلی، م.، و باقری، مجید.،1398، استفاده از فیلتر ساویتزکی-گولای برای ارتقا کیفیت تصاویر لرزهای، اولین همایش ملی پردازش سیگنال و تصویر در ژئوفیزیک، شاهرود،https://civilica.com/doc/970463 .
Ata, M., Abdelakder, E.M., Abouhamad, M., Serror, M.H., and Marzouk, M., 2017, On the Use of Ground Penetrating Radar, for Bridge Deck Assessment, International Conference on Computer Science and Application Engineering (CSAE 2017), ISBN: 978-1-60595-505-6.
Awal, M. A., Mostafa, S. S., and Ahmad, M., 2011, Performance analysis of Savitzky- Golay smoothing filter using ECG signal, International journal of computer information, 1 (2), 24-29.
Baba, K.,
Bahi, L.,
Ouadif, L., 2014, Enhancing Geophysical Signals Through the Use of Savitzky-Golay filtering method,
Geofísica Internacional, 53 (4), 399-409.
Baili, J., Lahouar, S., Hergli, M., Al-QadiI, L., and Besbes, K., 2009, GPR signal de-noising by discrete wavelet transform, Journal of NDT&E International, 42, 696-703.
Bednarczyk, Z., and Szynkiewicz, A., 2015, Applied Engineering Geology Methods for Exemplar Infrastructure Projects in Malopolskie and Podkarpackie Provinces, Springer International Publishing In Engineering Geology for Society and Territory, 6, 203-210.
Blackard, K.L., Rappaport, T. S., Bostian, C. W., 1993,
Measurements and models of radio frequency impulsive noise for indoor wireless communications, IEEE Journal on Selected Areas in Communications, 11 (7), 991-1001.
Breiman, L., 1995, better subset regression using the non-negative garrote, Technometrics, 37, 373-384.
Chen, Z., and Shu, J., 2011, remote sensing image merging based on Savitzky-Golay method, Geo- spatial Information Science, 27 (2), 29-33.
Chen, J., Jönsson, P., Tamura, M. Z. Matsushita, B., and Eklundh, L., 2004, A simple method for reconstructing a high-quality NDVI time-series data set based on the Savitzky–Golay filter, Remote Sensing of Environment. 91, 3-4, 332- 344.
Cheynet, E., 2020, Non-Gaussian process generation, MATLAB Central File Exchange, Retrieved,(https://www.mathworks.com/matlabcentral/fileexchange/52193-non-gaussian-process-generation).
Chui, C.K., 1992, An introduction to wavelet, New York: Academic Press, ISBN:10:0121745848, 266.
Daubechies, I., 1992, Ten lectures on wavelets, Society for Industrial and Applied Mathematics, ISBN: 0898712742,357.
Demirel, H., and Anbarjafari, G., 2010, Satellite image resolution enhancement using complex wavelet transform, Geoscienceand Remote Sensing Letters, IEEE 7, 1.123-126.
Donoho, D. L.,1995, De-noising by soft thresholding, IEEE transactions on information theory, 41, 613-627.
Donoho, D. L. Johnstone, I. M., 1994, Ideal spatial adaptation via wavelet shrinkage, Biometrika, 81, 425-455.
Ebrahimi Bardar, A., Oskooi, B., and Goudarzi, A ., 2019, comparison of GPR random noise attenuation using autoregressive-FX method and tunable quality factor wavelet transform TQWT with soft and hard thresholding, Journal of Signal and Information Processing, 10, 19-35.
Ferguson, R., and Margrave, G., 2012, attenuation compensation for georadar data by Gabor deconvolution, CREWES Research, Report 24.
Fontul, S., Fortunato, E., De Chiara, F., Burrinha, R., and Baldeiras, M., 2016, Railways Track Characterization Using Ground Penetrating Radar, The 3rdInternational Conference on Transportation Geotechnics (ICTG 2016), 143,1193-1200.
Gurley, K. R., Tognarelli, M. A., & Kareem, A. 1997, Analysis and simulation tools for wind engineering. Probabilistic Engineering Mechanics, 12(1), 9-31.
Jeng, Y.,
Li, Y.,
Chen, Ch.,
Chien, H., 2009, Adaptive filtering of random noise in near-surface seismic and ground-penetrating radar data,
Journal of Applied Geophysics,
68 (1), 36-46.
Jiao, L., Ye, Q., Cao, X., Huston, D., Xia, T., 2020, Identifying concrete structure defects in GPR image, Journal of Measurement, 160,
https://doi.org/10.1016/j.measurement.2020.107839.
Julayusefi, M., Goudarzi, A., Hozhabry, R., Shamounadeh, M, 2012, Application of the 2D dual tree CWT as an image processing technique to attenuate remnant random noise of GPR signal, SEG Technical Program Expanded Abstracts Istanbul 2012 International Geophysical Conference and Oil and Gas Exhibition.
Ishitsuka, K., Iso, Sh., Onishi, K., Matsuoka, T., 2018, Object Detection in Ground penetrating Radar Images using a deep convolutional neural network and image set preparation by migration, International journal of Geophysics,
https://doi.org/10.1155/2018/9365184.
Kingsbury, N. G., 1998, The dual-tree complex wavelet transform: a new efficient tool for image restoration and enhancement, Proc EUSIPCO. 98, 319-322.
Lahouar, S., 2003, Development of Data Analysis Algorithms for Interpretation of Ground Penetrating Radar Data. PhD Dissertation, Department of Electrical Engineering, Virginia Tech, Blacksburg.
Lamard, M., Daccache, M., Cazuguel, W., Roux, G., and Cochener, B., 2005, Use of a JPEG-2000 wavelet compression scheme forcontent-based ophthalmologic retinal images retrieval, inProc. 27th IEEE EMBS, 4010—4013.
Lejerowicz, A., Wysocka, A., Kowalczyk, S., 2018, Application of ground penetrating radar method combined with sedimentological analyses in studies of glaciogenic sediments in central Poland,
Studia Quaternaria, 38 (2), 103-119.
Liu, C. C., Dai, D. Q., and Yan, H., 2007, Local discriminantwavelet packet coordinates for face recognition,Journal of Machine Learning Research, 1165-1195.
Liu, Y., Dang, B., Li, Y., Lin, H., and Ma, H., 2016, Applications of Savitzky-Golay filter for seismic random noise reduction, Acta Geophysica, 64(1), 101-124.
Moghaddam, S., Oskooi, B., Goudarzi, A., and Azadi, A., 2019, The comparative sense of sparse deconvolution and least-squares deconvolution methods in increasing the temporal resolution of GPR data, Arabian journal of Geosciences, https://doi.org/10.1007/s12517-019-4686-4.
Oskooi, B., Parnow, S., Smirnov, M., Varfinezhad, R. & Yari, M., 2018, Attenuation of random noise in GPR data by image processing, Arabian Journal of Geosciences, 11, 677.
Oskooi, B., Julayusefi, M., and Goudarzi, A., 2015, GPR noise reduction based on wavelet thresholdings, Arabian Journal of Geosciences, 8, 2937–2951.
Press., W.H., and Teukolsky., S.A., 1990, savitky-golay smoothing filters, computers in physics, 669-672.
Raj, V. N. P., and Venkateswarlu, T., 2012, Denoising of medical images using dual tree complex wavelet transform, procedia technology, 4, 238-244.
Robinson, E.A., and Treitel, S., 1967, Principles of
digital Wiener filtering, Geophysical Prospecting,
15 (3), 311-332.
Savitzky, A., and Golay, M., 1964, Smoothing and differentiation, of data by simplified least squares procedures, Analytical Chemistry, 36, 1627-1639.
Schmelzbach, C., and Huber, E., 2015, Efficient Deconvolution of Ground-Penetrating Radar Data,IEEE Transctions on Geoscience and Remote Sensing, 53(9), 5209-5217.
Schafer.,R.W., 2011, what is a savitzky-Golay filter, IEE signal processing magazine,1053-5888.
Sejdic, E.; Djurovic, I.; Jiang, J., 2009, Time-frequency feature representation using energy concentration: An overview of recent advances, Digital Signal Processing, 19 (1): 153–183.
Selesnick, I. W., Baraniuk, R. G., and Kingsbury, N. G.,2005, The dual-tree complex wavelet transform, IEEE signal processing magazine, 22, 123-151.
Tudor Barbu, T., 2013, Variational Image Denoising Approach with Diffusion Porous Media Flow, Abstract and Applied Analysis, ,
doi:
10.1155/2013/856876.
Wang, Y., 2015, Frequencies of the Ricker wavelet,
Geophysics, 80, A31-A37.
Wu, Sh.,
Wang, Y., Di , Z., Chang, X., 2018, Random noise attenuation by 3D Multi-directional vector median filter,
Journal of Applied Geophysics,
159, 277-284.
Yang, Q., 2013, GPR detection for underground water pipe based on wavelet transform and matching pursuit algorithm, International Journal of advancements in computing technology, 5, 122-127.
Yang, Y., Tong, S., Huang, S., Pan, L.,2014, Dual-Tree Complex Wavelet Transformand Image Block Residual-Based Multi-Focus Image Fusionin Visual Sensor Networks, Sensors, 14 (2),22408-22430.
Yilmaz, Ö., 2001, Seismic data analysis. Tulsa, Society of Exploration Geophysicists, 1, 74170-2740.
Ziegler, H., 1981, Properties of digital smoothing polynomial (DISPO) filters, Applied Spectroscopy, 35, 88-92.
)