Open AccessSeismic Signal Filtering based on Pseudo Wigner-Ville Distribution and Catte Model
Author(s) -
Yan-Ping Liu,
Zenghong Ma,
Jia Huiqin,
Gao Jianshen
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1894/1/012058
Subject(s) - noise (video) , signal (programming language) , filter (signal processing) , algorithm , computer science , distribution (mathematics) , nonlinear filter , wigner distribution function , modulation (music) , enhanced data rates for gsm evolution , acoustics , mathematics , artificial intelligence , image (mathematics) , computer vision , physics , filter design , mathematical analysis , quantum mechanics , quantum , programming language
In practice, there are various noises included in the collected seismic data. As a common background noise, random noise may interfere even annihilate valid signals. In view of this, it needs to adopt effective methods to eliminate random noise as much as possible. This paper proposes a filtering method that is based on pseudo Wigner-Ville distribution (PWVD) and Catte model. PWVD is a windowed form of Wigner-Ville distribution (WVD) which can make the nonlinear signal to be locally linearized in addition to weakening the influence of cross item. And the Catte model is a kind of anisotropic diffusion algorithm which can eliminate the noise while protecting the edge of image. The implementation of the proposed method is to do PWVD for the frequency modulation form of noise-containing signal and then to filter the PWVD via Catte model, at last to adopt peak search to obtain the estimation of the valid signal.