کاربرد صافی گابور دوبعدی در تحلیل داده‌های مغناطیس هوابرد منطقة خرم‌آباد و مغناطیس زمینی در منطقة کاشمر

نوع مقاله : پژوهشی

نویسندگان

1 دانشجوی کارشناسی ارشد، گروه فیزیک، دانشکده علوم، دانشگاه رازی، کرمانشاه، ایران

2 استادیار، گروه فیزیک، دانشکده علوم، دانشگاه رازی، کرمانشاه، ایران

چکیده

روش‌های پردازش تصویر در پردازش داده‌های میدان پتانسیل به‌منظور آشکارسازی لبه‌های توده‌های بی‌هنجار مورد استفاده قرار می‌گیرند. در این تحقیق ابتدا صافی گابور دوبعدی معرفی می‌شود. سپس عملکرد صافی گابور بر داده‌های به‌دست آمده از سه منشور مغناطیده که در سه عمق و جهت مختلف قرار گرفته‌اند مورد بررسی قرار می‌گیرد. سپس اثرات تغییر طول‌موج، انحراف‌معیار و جهت‌گیری توده‌ها در عملکرد صافی گابور بر روی داده‌های حاصل از مدل‌های مصنوعی مورد بررسی قرار گرفته‌اند. بررسی‌ها نشان می‌دهند که صافی گابور یک صافی پایین‌گذر بوده و می‌تواند لبة بی‌هنجاری‌های را آشکارسازی کند. در نهایت صافی گابور بر داده‌های مغناطیس هوابرد منطقة خرم‌آباد در جنوب‌غرب ایران اعمال شده است. نتایج نشان می‌دهند که روند ساختارهای زمین‌شناسی در منطقة خرم‌آباد عمدتاً شمال‌غربی-جنوب‌شرقی می‌باشند که در تطابق با نتایجی است که از سایر صافی‌ها به‌دست آمده است. همچنین صافی گابور بر داده‌های زمینی یک تودة معدنی در منطقه کاشمر اعمال و لبة توده بی‌هنجار در این منطقه هم توسط صافی گابور تعیین شد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Application of 2D Gabor filter in analysis of the aeromagnetic data at Khoram Abad and ground magnetic data at Kashmar regions

نویسندگان [English]

  • Ehsan Fouladi 1
  • Mohsen Oveisy Moakhar 2
1 M.Sc. Student, Department of Physics, Faculty of Science, Razi University, Kermanshah, Iran
2 Assistant Professor, Department of Physics, Faculty of Science, Razi University, Kermanshah, Iran
چکیده [English]

Image processing techniques have been used in processing of potential fields data in order to delineate the edges of the anomalous sources. In this research, firstly the 2D Gabor filter was introduced. Then its operation was investigated on the three magnetized prisms which were at the three different depths and orientations. The effects of body wavelength, standard deviation and body orientation in the Gabor filter on the detection of edge bodies were studied. Investigations showed that the Gabor filter is a low pass filter. Afterwards, the Gabor filter was applied on the aeromagnetic data of Khoram Abad region in the southwest and ground magnetic data from Kashmar region in the northeast of Iran. The results show that the trend of geological structures is NW-SE which is in concordance to those obtained from other filters as well as geological map of the region.
1 2D Gabor filter
The boundary of the geological structures can be determined by processing of potential field spectrums .Most filters which have been used for edge detection are based on the different degree of derivatives. The derivatives cause noises and signals amplify together which decrease resolution of edges. Therefore, using filters without any derivative terms is a prime objective. The Gabor filter has not any derivative terms in its mathematical structure. Denis Gabor first introduced the filter for image processing. This filter is linear and has been used for analyzing details of an image or its texture. The characteristics of the Gabor filter is to obtain special frequencies in a certain point or a region. Mostly this filter has been used for analyzing human vision system. The Gabor filter has two parts, real and imaginary in exponential forms which are multiplied with a Gaussian function. The real part has been used for data filtering. The Gabor filter response in spatial domain is defined by convolution of data in the Gabor matrix. The Gabor filter is a low pass filter which attenuates noises while it detects the edges of the deep anomalies in a certain direction. The Gabor filter in mathematics is in the group of filter transformation. On this basis, this filter can process images in different directions and frequencies. The Gabor filter has many applications in image processing such as texture analysis, fingerprint detection, edge detection, document processing and so on. The 2D Gabor filter was also used for identification of the edges of the geological structures and faults. For determination of the geological trends and faults, we must apply the Gabor filter in different directions and frequencies and standard deviations. In this article, we first introduce the Gabor filter and its characteristics. Afterwards this filter is applied on the aeromagnetic data from Khoram Abad and ground magnetic from an iron mine at Kashmar regions in the the southwest and northeast of Iran respectively. 
2 The real data
We prepared the following maps from the real data in Khoram Abad region: the map of the total magnetic intensity, the reduction to the pole of aeromagnetic map and the map resulted from the application of the Gabor filter on the residual aeromagnetic map of the region. From the latter map, the trend and edges of the geological structures were identified. The other trends may be detected by changing the various parameters of the filter specially its direction. The trend of the geological structures which is revealed by the Gabor filter is northwest- southeast. If the Gabor filter is applied with the other edge filters such as derivative of tilt angle, analytic signal filters, we can identify the boundaries better. The Gabor filter on the data from Kashmar region, delineates the boundary of the iron ore body at the studied area.

کلیدواژه‌ها [English]

  • Gabor filter
  • Potential Field
  • Khoram abad
  • aeromagnetic
  • low pass filters
  • Edge detection
یوسفی، ا.، 1373، نقشه  خطواره‌های مغناطیسی ایران، سازمان زمین‌شناسی و اکتشافات معدنی ایران.
Ackerman, H. A. and Hewitt Dix, C., 2002, The first vertical derivative of gravity. Geophysics. 20. 148-154.
Baranov, V. and Naudy, H., 1964, Numerical calculation of the formula of reduction to the magnetic pole. Geophysics, 29. 67-69.
Cooper, G. R. J. and Cowan. D. R., 2004, Filtering using variable order vertical derivatives. Computers and Geosciences. 30. 455-459.
Daugman, J. G., 1988, Complete discrete 2-D Gabor transforms by neural networks for image analysis and compression. signal processing. 36. 1169-1179.
Holden, E., Dentith, M. and Kovesi, P., 2008, Toward the automated analysis of regional aeromagnetic data to identify regions prospective for gold deposits, Computers and Geosciences. 34. 1505-1513.
Ma, G. and Li, L., 2012, Edge detection in potential fields with the normalized total horizontal derivative. Computers and Geosciences. 41. 83-87.
Ma, G. and Du, X., 2012, An improved analytic signal technique for the depth and structural index from 2D magnetic anomaly data. Pure and Applied Geophysics. 169. 2193-2200.
Mehrotra, R., Namuduri, K. R. and Ranganathan, N., 1992, Gabor filter –based edge detection, Pattern Recognition. 25.1479-1494.
Miller, H. G. and Singh, V., 1994, Potential field tilt- a new concept for location of potential field sources. Journal of Applied Geophysics. 32. 213-217.
Nabighian, M. N., 2012, The analytic signal of two - dimensional magnetic bodies with polygonal cross-section : its properties and use for automated anomaly interpretation. Geophysics. 37. 507-517.
Prewitt, J., 1970, Object enhancement and extraction , in Lipkin, B.S.,Rosenfeld, A. Eds. picture processing and psychopictorics: Academic press. NY. 75-149.
Roberts, L. G., 1965, Machine perception of three dimensional solids, in Tippet, J.T., Eds., Optical and electro-optical information processing: MIT press. MA. 159-197.
Roslan, R. and Jamil, N., 2012, Texture feature extraction using 2D Gabor filters, International symposium on computer applications and industrial electronics. IEEE. DOI: 10.1109/ISCAIE.2012.6482091.
Sertcelik, I., Kafadar, O. and Kurtulus, C., 2013, Use of the two dimensional Gabor filter to interpret magnetic data over the Marmara sea Turkey, Pure and Applied Geophysics. 170. 887-894.
Sobel, I., 1970, Camera model and perception: Ph.D. thesis . Stanford University. Stanford. California.
Sobel, I., 1990, An isotropic 3*3 gradient operator, in Freeman,H., Eds., machine vision for three dimensional scenes: Academic press. NY. 376-379.
Wijns, C., Perez, C. and Kowalczyk, P., 2005, Theta map: Edge detection in magnetic data, Geophysics. 70. L39-L43.