Mask filtering to the Wigner-Ville distribution
Haifa AlSalmi, Yanghua Wang
Abstract
ABSTRACT The Wigner-Ville distribution (WVD) is a high-resolution time-frequency spectral analysis method for nonstationary signals; yet, it suffers from cross-term interference among signal components. We proposed applying a masking filter directly to the WVD time-frequency spectrum to suppress the cross-term interference. Conventional methods for suppressing interference include the smoothed pseudo-WVD (SP-WVD) method, which incorporates smooth filtering in the time and frequency directions. We exploited the SP-WVD spectrum as a reference to design the masking filter; thus, the mask-filtered WVD (MF-WVD) procedure is data-adaptive. The MF-WVD method preserves the high-resolution energy concentration in the spectrum portrayed by the standard WVD, while suppressing the cross-term interference cleanly as in the SP-WVD method. Applying the MF-WVD method to field 3D seismic data generates high-resolution spectral cubes for various frequencies, and these spectral cubes may be used intuitively for detecting reservoir-related characteristics.