Edge recognition using joint correlation coefficient of gravity gradient
HOU Zhenlong1,2, YUAN Yuan3, WANG Ende1,2, FU Jianfei1,2, ZHENG Yujun1
1. Key Laboratory of Ministry of Education on Safe Mining of Deep Metal Mines, Northeastern University, Shenyang, Liaoning 110819, China; 2. College of Resources and Civil Engineering, Northeastern University, Shenyang, Liaoning 110819, China; 3. Key Laboratory of Submarine Geosciences, Se-cond Institute of Oceanography, Ministry of Natural Resources, Hangzhou, Zhejiang 310012, China
Abstract：To improve the quality of gravity gradient ima-ging and resolution of identifying subsurface structure boundaries,we use the joint correlation coefficient of total horizontal derivative in x and y direction with gravity gradient for edge recognition.Correlation coefficients calculated at multi-directional windows are integrated to enhance image.Binarization and thresholding are also utilized to highlight edges.Model tests show that model boundaries,especially the corners,could be clearly imaged.We apply this method to the aerial data observed at the Bay St.George's,Canada and identify major subsurface structure boundaries.The tests demonstrate the feasibility of the method.We also discuss the impacts of window size,observation point spacing,and line spacing on imaging.Compared with other methods,the method is theoretically simple and can yield better image.
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