小波变换与地震数据压缩
|
摘要
本文详细介绍了小波变换的基本理论及离散信号多分辨率分析的一种具体实现方法（即金字塔算法），并据此提出了一种基于小波变换的地震数据压缩算法。多个数据集的压缩／重建处理表明本方法效果很好，通常情况下压缩比可达8：1～16：1左右。
The paper gives a presentation of the philosophy for wavelet transform and the approach on the multiresolution analysis for discrete signals (i. e. the pyramid algorithm). In what follows an algorithm for seismic data compression is presented based on the wavelet transform technique, of which the effectivity was verified via an experiment of data compression and reconstruction on several data sets. Usually, the compression ratio able to be reached is in the range of 8: 1~ 16: 1.
The paper gives a presentation of the philosophy for wavelet transform and the approach on the multiresolution analysis for discrete signals (i. e. the pyramid algorithm). In what follows an algorithm for seismic data compression is presented based on the wavelet transform technique, of which the effectivity was verified via an experiment of data compression and reconstruction on several data sets. Usually, the compression ratio able to be reached is in the range of 8: 1~ 16: 1.
引文
[1] P. Goupilloud, A. Grossmann, and J. Morlet, Cycle-octave and related trans forms in seismicsignal analysis,Geophysics,Vol. 23,No. 1, 1984.
[2] A. Grossmann and R. Kronland-Martinet,Time-and-scale representations obtained throughcontinuous wavelet transforms,in Signal Processing Ⅳ:Theories and Applications, ed. J. L.Lacoume,et al-, Elsevier Science Publisher B. V.,1988.
[3] R. Kronland-Martinet,The wavelet transform for analysis,synthesis,and processing of speechand music sounds, Computer Music Journal,Vol. 12,No. 4, 1988.
[4] S, G. Mallat, A theory for multiresolution signal decomposition: the wavelet representation,IEEE Trans-PAMI,Vol. 11,No. 7, 1989.
[5] A. Grossmann, R. Kronland-Martinet, and J. Morlet, Reading and understanding continuouswavelet transforms, in Wavelets,Time-Frequency Representations and Plane Space,ed. J. M.Combes,et al., Springer Verlag, 1989.
[6] Yi Lu and G. T. Schuster,Wave packet transform and data compression,SEG 第62届年会论文集, 1992年。
[7] D. A. Stcinlein and O. Hjelle,Compact digital representation of seismic signals, SEG第62届年会议文体, 1992年。
[8] C. Bosman and E. Reiter,Seismic data compression using wavelet transforms,SEG 第63届年会论文集,1993年
[9] 朱光明、高静怀、王玉贵,小波变换及其在一维滤波中的应用,《石油物探》,第 32卷,第1期,1993年。
[10] 谢凤兰、赵改善,用SVD算法提高地震剖面的信噪比,《石油物操》,第29卷,第4期,1990年。
[2] A. Grossmann and R. Kronland-Martinet,Time-and-scale representations obtained throughcontinuous wavelet transforms,in Signal Processing Ⅳ:Theories and Applications, ed. J. L.Lacoume,et al-, Elsevier Science Publisher B. V.,1988.
[3] R. Kronland-Martinet,The wavelet transform for analysis,synthesis,and processing of speechand music sounds, Computer Music Journal,Vol. 12,No. 4, 1988.
[4] S, G. Mallat, A theory for multiresolution signal decomposition: the wavelet representation,IEEE Trans-PAMI,Vol. 11,No. 7, 1989.
[5] A. Grossmann, R. Kronland-Martinet, and J. Morlet, Reading and understanding continuouswavelet transforms, in Wavelets,Time-Frequency Representations and Plane Space,ed. J. M.Combes,et al., Springer Verlag, 1989.
[6] Yi Lu and G. T. Schuster,Wave packet transform and data compression,SEG 第62届年会论文集, 1992年。
[7] D. A. Stcinlein and O. Hjelle,Compact digital representation of seismic signals, SEG第62届年会议文体, 1992年。
[8] C. Bosman and E. Reiter,Seismic data compression using wavelet transforms,SEG 第63届年会论文集,1993年
[9] 朱光明、高静怀、王玉贵,小波变换及其在一维滤波中的应用,《石油物探》,第 32卷,第1期,1993年。
[10] 谢凤兰、赵改善,用SVD算法提高地震剖面的信噪比,《石油物操》,第29卷,第4期,1990年。
版权所有：© 2023 中国地质图书馆 中国地质调查局地学文献中心