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随着小波理论的发展与应用，小波变换已成为信号分析处理的一种强有力的新工具。本文根据M带小波变换理论，结合地震数据的特征，将M带小波变换应用于地震数据的压缩处理，提出了地震数据的压缩编码算法。其压缩过程为：首先对地震数据进行二维M带小波分解，形成由小波变换系数构成的分频剖面;然后对各子带中的细节分量进行阈值取舍，保留有用的细节分量而会去无用的或对原始数据贡献较小的成分;再采用自适应方法对所剩的M带小波变换系数进行尺度量化;最后采用算术编码进行熵编码，完成地震数据的压缩编码全过程。数据重建可通过作解码、反量化、利用M带小波逆变换实现之。实验结果表明，该方法简单、易操作，对地震数据压缩行之有效，压缩比可达10～30。
With the development and application of wavelet theory, wavelet transform has become a powerful new tool for signal analysis and processing. According to the theory of M-band wavelet transform, combined with the characteristics of seismic data, the M-band wavelet transform is applied to the seismic data compression processing, and the seismic data compression coding algorithm is proposed. The compression process is as follows: firstly, the two-dimensional M-band wavelet decomposition of seismic data is performed to form a frequency-divided profile composed of wavelet transform coefficients; then the threshold components of the detail components in each sub-band are selected and the useful detail components are reserved, Or the components that contribute less to the original data. Then, the remaining M-band wavelet transform coefficients are quantized by adaptive method. Finally, the whole process of compressing and encoding the seismic data is completed by entropy coding by using the arithmetic coding. Data reconstruction can be done by decoding, inverse quantization, using M-band inverse wavelet transform. The experimental results show that the proposed method is simple and easy to operate, and can effectively compress the seismic data with a compression ratio of 10-30.