Potential field gradient modulus maxima edge detection based on wavelet transform

摘要

As the Fourier transform only can confirm the overall nature of the signal singularity, especially in analyzing the geological body edges (for instance, the deep faults) for the upward extended signal, the detected edges from the horizontal total gradient modulus that based on the Fourier transform are often blurred and smooth, so it is difficulties to confirm the details of the edges. The wavelet transform is with the good time-frequency localization, and its coefficient gradient maxima are very sensitive to the signal singular, which can be used to analyze the signal singular points location and singularity degree. We proposed a potential field gradient modulus maxima edge detection method that based on wavelet transform, which utilizes the horizontal gradient variation of the wavelet transform coefficient to synthesize the wavelet gradient modulus, and with the modulus maxima to perform the edges detection. The theoretical model tests and the practical fault analysis for the Middle-Lower Reach of Yangtze River indicates the outcomes with proposed method is of higher resolution as well as stronger anti-jamming capability than those from the horizontal total gradient modulus and its maxima that based on the Fourier transform.