Research Article
BibTex RIS Cite

Application of Image Processing Methods to Geophysical Maps: Examples From Archaeogeophysical Investigations

Year 2022, Volume: 43 Issue: 2, 160 - 181, 28.07.2022
https://doi.org/10.17824/yerbilimleri.1006057

Abstract

References

  • Akca I., Balkaya Ç., Pülz A., Alanyalı H.S., Kaya M.A. 2019. Integrated geophysical investigations to reconstruct the archaeological features in the episcopal district of Side (Antalya, Southern Turkey). Journal of Applied Geophysics, 163, 22-30.
  • Akca I., Balkaya Ç., Pülz, A. Alanyalı, H.S., ve Kaya M.A. 2018. Side Antik Kentinde Yürütülen (Antalya, Türkiye) Jeofizik Araştırmalar. 7. Yer Elektrik Çalıştayı, 7-9 Mayıs 2018, Eğirdir, Isparta.
  • Akca I., Lallı, S., S. Patara Jeofizik İnceleme Raporu. 2019. Ankara Üniversitesi
  • Al Nuamy, W., Huang, Y., Nakhkash, M., Fang, M.T.C., Nguyen, V.T., Eriksen, A., 2000. Automatic detection of buried utilities and solid objects with GPR using neural networks and pattern recognition. Journal of Applied Geophysics, 43, 157-165.
  • Arısoy, MO., Dikmen, Ü., 2015 Edge enhancement of magnetic data using fractional-order-derivative filters, Geophysics, 80 (1), J7-J17.
  • Ayers G. R., Dainty G., R. Iterative Blind Deconvolution Method and It’s Application. 1988. Optics Letters. 13, 547-549.
  • Bergeron, S. Y, Yuen D. A, Vincent, A. P., (2000a), Capabilities of 3-D wavelet Transforms to detect plume-like structures from seismic tomography, Geophysical Research Letters 26:2311-2314
  • Buades, A., Coll, B., Morel, J. M. 2005. A non-local algorithm for image denoising. Proc. of IEEE CVPR, 2, 60–65.
  • Buades, A., Coll, B., Morel, J. 2005. A review of image denoising algorithms, with a new one. Multiscale Modeling and Simulation: A SIAM Interdisciplinary Journal, Society for Industrial and Applied Mathematics, 4 (2), 490-530.
  • Carrato S., Ramponi G., Marsi S., Jerian M., Tenze L. FPGA Implementation of the Lucy Richardson Algorithm For Fast Space Variant Image Deconvolution. 2015. 9th International Symposium of Image and Signal Processing and Analysis (ISPA). 15, 137-142.
  • Carter, N., Lines, L., 2001. Fault imaging using edge detection and coherency measures on Hibernia 3-D seismic data. The Leading Edge, 20 (01), 64-69.
  • Chen, S. D., Ramli A. R., “Minimum mean brightness error bi-histogram equalization in contrast enhancement,”. 2003. IEEE Trans. Consum. Electron., 49(9), 1310–1319.
  • Demanent D., Pirard E., Renardy F. Jongmans D. “Application and processing of geophysical images for mapping faults” Computers & Geosciences 27 (2001) 1031-1037
  • Dhawan A., P., Rangayyan, Rangaraj, M., Gordon., R. Image Restoration by Wiener Deconvolution in Limited View Computed Tomography. 1986. Applied Optics. 24(23), 4013-4020.
  • Gandomi, A., H., Alavi, A., H. Krill Herd: A New Bio-Inspired Optimization Algorithm. 2012. Comminications in Nonlinear Science and Numerical Simulation. 17(12), 4831-4845.
  • Gölebatmaz, Ş., M. 2020. Jeofizik Modellerin ve Haritaların Görüntü İşleme Yöntemleri ile İyileştirilmesi. Ankara Üniversitesi, Fen Bilimleri Enstitüsü, Jeofizik Mühendisliği Anabilim Dalı, Ankara
  • Ilesanmi, A., E., Ilesanmi, T., O. Methods for Image Denoising Using Convolutional Neural Network: A review. Complex and Intelligent Systems
  • King, M., A., Miller, T., R. Use of nonstationary temporal Wiener filter in nuclear medicine. 1985. Europian Journal of Nuclear Medicine. 10. 458- 461.
  • Kuruc, A., Treves, S., Parker, J., A., Cheng, C., Sawan, A. 1983. An improved deconvolution technique for improvement after suboptimal bolus injection. Radiology. 148. 233-238.
  • Lili, Z. Tianyoao, H., Jianshemg, W. and Jialin, W. 2005. Application of Image Enhancement Techniques to Potential Field Data. Applied Geophysics, 2, 3, 145-152.
  • Lucas, A., Illiadis, M., Molina, R., Katsaggelos, A., K. 2018. Using Deep Neural Networks for Inverse problems in Imaging: Beyond Analytical Methods. IEEESignal Process Mag 35(1). 20-36
  • Marques, O. 2011. Practical imahe and video processing using MATLAB. Wiley IEEE Press, 639, US
  • Moffat., F., J. A theoretical investigation of focal stellar images in the photographic emulsion and application to photographic photometry. 1969. Astronomy and Astrophysics. 3. 455–461.
  • Morozov, I. B., and Smithson, S. B. (1996), Instantaneous Polarization Attributes and Directional Filtering, Geophysics 61, 872-881.
  • Nguyen F., Garambois S., Jongmans D., Pirard E., Loke M.H. “Image processing of 2D resistivity data for imaging faults.” Journal of Applied Geophysics 57 (2005) 260-277.
  • Panagiotakis, C., Kokinou, E. and Sarris, A. 2011. Curvilinear Structure Enhancement and Detection in Geophysical Images. IEEE Transactions on geoscience and remote sensing 49,6, 2040-2048.
  • Rao, D., S., Deepthi, K. S., Deep, K. M. S. 2011. Application of Blind Deconvolution Algorithm for Image Restoration. International journal of Engineerin Science and Technology (IJEST), 3(3), 1878-1884.
  • Richardson W., H. 1972 Bayesian-based Itaretive method of image restoration. Journal of Optical Society of America. 62(1) 55-59
  • Sarker S., Chowdhury S., Laha S., Dey D. 2012. Use of Non-Local Means Filter to Denoise Image Corrupted by Salt and Pepper Noise. Signal and Image Processing : An International Journal, 3(2), 223-235.
  • Tsumuraya, N., M., F., Baba., N. Iterative blind deconvolution method using Lucy’s algorithm. 1994. Astronomy and Astrophysics. 282 (2), pp. 699–708.
  • Zhang, K., Wangmeng, Z., Chen, Y., Meng, D., Zhang, L. 2016. Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising. IEEE Transactions on Image Processing. 26(7). 3142-3155

Görüntü İşleme Yöntemlerinin Jeofizik Haritalara Uygulanması: Arkeoloji Jeofiziği Alanından Örnekler

Year 2022, Volume: 43 Issue: 2, 160 - 181, 28.07.2022
https://doi.org/10.17824/yerbilimleri.1006057

Abstract

Uygulamalı jeofizik yöntemler ile belirli bir fizik parametresinin yerdeki dağılımına bağlı olarak yer içinin olanaklı en net görüntüsü elde edilmeye çalışılır. Bu amaçla farklı fizik ilkelerine dayanan yöntemlerle yapılan ölçümlere ait veriler, çeşitli veri işlem adımlarından geçirilerek kesit, harita ve modeller halinde görsel veya sayısal olarak sunulurlar. Yöntemlerin ve sayısal işlemlerin doğası gereği son adımda sunulan sonuçlarda yalancı belirtiler, asıl belirtiyi örten gürültüler ve bozulmalar görülebilir. Bu sorunun üstesinden gelmek ve jeofizik haritaları daha kolay yorumlanabilir hale getirmek amacıyla görüntü işleme yöntemlerinden faydalanılabilir. Görüntü işleme giderek gelişen ve uygulama konuları artan bir alandır. Bu çalışmanın konusu, görüntü işleme yöntemlerinin jeofizik harita ve görüntülerin iyileştirilmesi için kullanılmasını kapsamaktadır. Çok sayıda yöntemden seçilen görüntü işleme uygulamaları, gürültü giderme ve netleştirme süzgeçleri ile morfolojik süzgeçler genel olarak tanıtılmış ve yakın yüzey jeofizik araştırmalardan elde edilen görüntülere uygulanarak sonuç ve etkinlikleri tartışılmıştır. Uygulama açısından daha belirgin sonuçlar üreteceğinden, çizgisellik ve yapısal unsurlar içeren arkeoloji jeofiziği çalışmalarına ait jeofizik sonuçlar tercih edilmiştir. Yapılan uygulamalar ile istenilen özelliklerin öne çıkarılması ya da istenmeyen özelliklerin bastırılması konusunda başarılı sonuçlar elde edilmiştir.

References

  • Akca I., Balkaya Ç., Pülz A., Alanyalı H.S., Kaya M.A. 2019. Integrated geophysical investigations to reconstruct the archaeological features in the episcopal district of Side (Antalya, Southern Turkey). Journal of Applied Geophysics, 163, 22-30.
  • Akca I., Balkaya Ç., Pülz, A. Alanyalı, H.S., ve Kaya M.A. 2018. Side Antik Kentinde Yürütülen (Antalya, Türkiye) Jeofizik Araştırmalar. 7. Yer Elektrik Çalıştayı, 7-9 Mayıs 2018, Eğirdir, Isparta.
  • Akca I., Lallı, S., S. Patara Jeofizik İnceleme Raporu. 2019. Ankara Üniversitesi
  • Al Nuamy, W., Huang, Y., Nakhkash, M., Fang, M.T.C., Nguyen, V.T., Eriksen, A., 2000. Automatic detection of buried utilities and solid objects with GPR using neural networks and pattern recognition. Journal of Applied Geophysics, 43, 157-165.
  • Arısoy, MO., Dikmen, Ü., 2015 Edge enhancement of magnetic data using fractional-order-derivative filters, Geophysics, 80 (1), J7-J17.
  • Ayers G. R., Dainty G., R. Iterative Blind Deconvolution Method and It’s Application. 1988. Optics Letters. 13, 547-549.
  • Bergeron, S. Y, Yuen D. A, Vincent, A. P., (2000a), Capabilities of 3-D wavelet Transforms to detect plume-like structures from seismic tomography, Geophysical Research Letters 26:2311-2314
  • Buades, A., Coll, B., Morel, J. M. 2005. A non-local algorithm for image denoising. Proc. of IEEE CVPR, 2, 60–65.
  • Buades, A., Coll, B., Morel, J. 2005. A review of image denoising algorithms, with a new one. Multiscale Modeling and Simulation: A SIAM Interdisciplinary Journal, Society for Industrial and Applied Mathematics, 4 (2), 490-530.
  • Carrato S., Ramponi G., Marsi S., Jerian M., Tenze L. FPGA Implementation of the Lucy Richardson Algorithm For Fast Space Variant Image Deconvolution. 2015. 9th International Symposium of Image and Signal Processing and Analysis (ISPA). 15, 137-142.
  • Carter, N., Lines, L., 2001. Fault imaging using edge detection and coherency measures on Hibernia 3-D seismic data. The Leading Edge, 20 (01), 64-69.
  • Chen, S. D., Ramli A. R., “Minimum mean brightness error bi-histogram equalization in contrast enhancement,”. 2003. IEEE Trans. Consum. Electron., 49(9), 1310–1319.
  • Demanent D., Pirard E., Renardy F. Jongmans D. “Application and processing of geophysical images for mapping faults” Computers & Geosciences 27 (2001) 1031-1037
  • Dhawan A., P., Rangayyan, Rangaraj, M., Gordon., R. Image Restoration by Wiener Deconvolution in Limited View Computed Tomography. 1986. Applied Optics. 24(23), 4013-4020.
  • Gandomi, A., H., Alavi, A., H. Krill Herd: A New Bio-Inspired Optimization Algorithm. 2012. Comminications in Nonlinear Science and Numerical Simulation. 17(12), 4831-4845.
  • Gölebatmaz, Ş., M. 2020. Jeofizik Modellerin ve Haritaların Görüntü İşleme Yöntemleri ile İyileştirilmesi. Ankara Üniversitesi, Fen Bilimleri Enstitüsü, Jeofizik Mühendisliği Anabilim Dalı, Ankara
  • Ilesanmi, A., E., Ilesanmi, T., O. Methods for Image Denoising Using Convolutional Neural Network: A review. Complex and Intelligent Systems
  • King, M., A., Miller, T., R. Use of nonstationary temporal Wiener filter in nuclear medicine. 1985. Europian Journal of Nuclear Medicine. 10. 458- 461.
  • Kuruc, A., Treves, S., Parker, J., A., Cheng, C., Sawan, A. 1983. An improved deconvolution technique for improvement after suboptimal bolus injection. Radiology. 148. 233-238.
  • Lili, Z. Tianyoao, H., Jianshemg, W. and Jialin, W. 2005. Application of Image Enhancement Techniques to Potential Field Data. Applied Geophysics, 2, 3, 145-152.
  • Lucas, A., Illiadis, M., Molina, R., Katsaggelos, A., K. 2018. Using Deep Neural Networks for Inverse problems in Imaging: Beyond Analytical Methods. IEEESignal Process Mag 35(1). 20-36
  • Marques, O. 2011. Practical imahe and video processing using MATLAB. Wiley IEEE Press, 639, US
  • Moffat., F., J. A theoretical investigation of focal stellar images in the photographic emulsion and application to photographic photometry. 1969. Astronomy and Astrophysics. 3. 455–461.
  • Morozov, I. B., and Smithson, S. B. (1996), Instantaneous Polarization Attributes and Directional Filtering, Geophysics 61, 872-881.
  • Nguyen F., Garambois S., Jongmans D., Pirard E., Loke M.H. “Image processing of 2D resistivity data for imaging faults.” Journal of Applied Geophysics 57 (2005) 260-277.
  • Panagiotakis, C., Kokinou, E. and Sarris, A. 2011. Curvilinear Structure Enhancement and Detection in Geophysical Images. IEEE Transactions on geoscience and remote sensing 49,6, 2040-2048.
  • Rao, D., S., Deepthi, K. S., Deep, K. M. S. 2011. Application of Blind Deconvolution Algorithm for Image Restoration. International journal of Engineerin Science and Technology (IJEST), 3(3), 1878-1884.
  • Richardson W., H. 1972 Bayesian-based Itaretive method of image restoration. Journal of Optical Society of America. 62(1) 55-59
  • Sarker S., Chowdhury S., Laha S., Dey D. 2012. Use of Non-Local Means Filter to Denoise Image Corrupted by Salt and Pepper Noise. Signal and Image Processing : An International Journal, 3(2), 223-235.
  • Tsumuraya, N., M., F., Baba., N. Iterative blind deconvolution method using Lucy’s algorithm. 1994. Astronomy and Astrophysics. 282 (2), pp. 699–708.
  • Zhang, K., Wangmeng, Z., Chen, Y., Meng, D., Zhang, L. 2016. Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising. IEEE Transactions on Image Processing. 26(7). 3142-3155
There are 31 citations in total.

Details

Primary Language Turkish
Subjects Engineering
Journal Section Articles
Authors

Şerif Murat Gölebatmaz 0000-0002-7321-5171

İrfan Akca 0000-0002-4229-2705

Publication Date July 28, 2022
Submission Date October 15, 2021
Acceptance Date April 8, 2022
Published in Issue Year 2022 Volume: 43 Issue: 2

Cite

EndNote Gölebatmaz ŞM, Akca İ (July 1, 2022) Görüntü İşleme Yöntemlerinin Jeofizik Haritalara Uygulanması: Arkeoloji Jeofiziği Alanından Örnekler. Yerbilimleri 43 2 160–181.