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本文讨论了第二代小波变换的基本原理和变换过程,并将第二代小波变换引入到地震资料去噪处理中,基于提升法的小波变换是一种柔性的小波构造方法,它使用线性、非线性或空间变化的预测和更新算子,并能确保变换的可逆性。通过对模拟数据和实际资料的处理,证明了的它对地震信号去噪具有很好的效果。离散信号的小波去噪可分为三步:小波分解,系数缩减(切除噪声部分),信号重建。目前常用的小波去噪的方法有硬阈值法和软阈值法,这里采用软阈值法去噪。本文的提升变换采用的是Deslauriers-Dubuc(4,2)小波,基于以上变换方法,分别对含噪的模拟数据及实际地震数据进行3级可逆提升变换,对每一级上的细节信号按上述的软域值法进行处理,削减小波系数中的噪声部分,从而实现了信号去噪,结果证明去除随机噪声的效果是令人满意的。
This paper discusses the second generation of wavelet transform the basic principles and transformation process, and the second generation of wavelet transform to the seismic data denoising processing, lifting method based on wavelet transform is a flexible method of wavelet construction, which uses linear, Nonlinear or spatial change prediction and update operator, and to ensure the reversibility of the transform. Through the processing of simulation data and actual data, it is proved that it has good effect on seismic signal denoising. Discrete signal wavelet denoising can be divided into three steps: wavelet decomposition, coefficient reduction (cutting noise part), signal reconstruction. The commonly used methods of wavelet denoising are hard threshold method and soft threshold method, here using soft threshold denoising method. In this paper, the Deslauriers-Dubuc (4,2) wavelet is used to enhance the transformation. Based on the above transformation method, three levels of invertible lifting transformation are respectively performed on the noisy simulation data and the actual seismic data. For each level, Of the soft-domain value method for processing, reducing the noise part of the wavelet coefficients to achieve the signal denoising, the results show that the effect of removing random noise is satisfactory.