A Seismic Signal Denoising Method Based on Wavelet Comprehensive Threshold

The wavelet comprehensive threshold is used to inherit and develop the advantages of hard threshold and soft threshold denoised method. Based on the small wavelet coefficients of the noise signal and the large wavelet coefficients of the seismic signal, the simulation experiment of the Ricker signal and the noise reduction experiment is carried out. The simulation results show that the MSE of the wavelet comprehensive threshold is the closest to the original signal waveform after noise reduction, and the energy of the high frequency part of the waveform is reduced and the low frequency part is suppressed. Finally, the actual seismic waveform, for example, the noise reduction of the actual waveform can be the first time of the waveform, and the waveform of the effective signal energy, noise signal energy is suppressed

Wavelet based Signal De-noising via Simple Singularities Approximation

In this paper WISDOW (wavelet-based image and signal de-noising via overlapping waves) is presented. It consists of a novel model for noise removal using wavelets. Its main peculiarity is the modelling of a noisy signal as composition of elementary atoms which behave as interfering waves in the wavelet domain. Signal recovery is then performed by means of the overlapping effects principle at each scale level. Early theoretical and experimental results show the great potential of the proposed model