Research On Multi-Scale Decomposition Of Wavelet Threshold Selection Method

Seismic data improve the signal to noise ratio is an important task of the digital processing of seismic signals. Therefore, seismic data denoising method of seismic exploration has been a hot area of research. With the develop of the digital signal processing technology, Many of the best methods of denoising coming to the fore, How to combine the characteristics of seismic data , Use appropriate methods to improve the noise signal to noise ratio of seismic data, Has important practical significance.This article, based on the traditional hard and soft threshold denoising algorithm functions carried out in-depth study and discussion, According to the lack of traditional threshold algorithm made a combination of hard and soft threshold denoising algorithm functions, The new threshold function is applied to one-dimensional and two-dimensional seismic signal denoising, Compare with the one-dimensional wavelet function under the new threshold with the soft and hard functions multi-threshold threshold selection in case of de-noising algorithms, Compare with Two-dimensional seismic images of the new threshold function and multi-function soft-threshold threshold selection in case of de-noising algorithms, The new threshold denoising algorithm improve the function of the traditional methods, increase signal to noise ratio and the fidelity of the results.