Li Hongxing1, Rao Shuo2, Tao Chunhui3, Zhou Jianping3, Zhang Hua1
1. School of Nuclear Engineering and (GHT) Geophysics, East China University of Technology, Nanchang, Jiangxi 330013, China;
2. School of Geophysics, Chengdu University of Technology, Chengdu, Sichuan 610059, China;
3. Second Institute of Oceanography, State Oceanic Administration, Hangzhou, Zhejiang 310012, China
Abstract:Conventional edge detection methods have low resolution and serious noise influence. Therefore we propose a new edge detection approach by introducing 2-D edge-preserved smoothing and generalized Hilbert transform (GHT) edge prediction. First edge-preserved smoothing processing is carried out. And then optimized windowed Fourier transform is conducted. Finally imaginary part absolute values of the transform are used to detect edges along 1/N power of the frequency sum of the windowed Fourier transform. This approach is applied to effectively predict the distribution of structural fracture and Karst pores and caves. Model and real data test results show that the proposed edge detection approach has not only strong noise-suppressed capacity but also high precision.
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