基于形态小波的地震数据压缩方法研究
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摘要
研究了地震勘探回波数据的压缩技术,针对地震信号形态纹理明显的特点,采用形态为主、小波为辅的分析方法取代单一的小波分析来研究地震信号的潜在规律,设计了基于形态变换的新一代地震数据压缩算法。
With the development of multi-dimensional and high-resolution about seismic exploration technology,and the expansion of seismic data rapidly,the problem of compression is more and more important.The compression technology of seismic exploration echo data has been studied in the paper.The analysis method adopted morphology manly and wavelet assistantly substitutes the single wavelet analysis to the potential rule research of seismic signal aimed at the distinct morphological grain characteristic of seismic signal,and the new generation seismic data compression algorithm based on morphological wavelet been designed.
With the development of multi-dimensional and high-resolution about seismic exploration technology,and the expansion of seismic data rapidly,the problem of compression is more and more important.The compression technology of seismic exploration echo data has been studied in the paper.The analysis method adopted morphology manly and wavelet assistantly substitutes the single wavelet analysis to the potential rule research of seismic signal aimed at the distinct morphological grain characteristic of seismic signal,and the new generation seismic data compression algorithm based on morphological wavelet been designed.
引文
[1]张玉芬.反射波地质勘探原理和资料解释[M].北京:地质出版社,2007:25-29
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[9]Li Feipeng,Ma Guoru,Qin Qianqing,et al.PriorImportant Band Hyper-spectral Image Compression[C].SPIE Proceedings,Multispectral ImageProcessing and Pattern Recognition,Beijing,2003
[10]Heijmans H J A M,Boutsias J.ConstructingMorphological Wavelets with the Lifting Scheme[C].The Fifth International Conference on PatternRecognition and Information Processing(PRIP’99)Minsk,Belarus,1999
[11]Sweldens W.The Liftin Scheme:a Custom-designConstruction of Biorthogonal Wavelets[J].Appliedand Computational Harmonic Analysis,1996(3):186-200
[2]Yilmaz O Z.Seismic Data Analysis[M].USA:Society of Exploration Geophysicists,2001:127-132
[3]Mallat S.A Theory for Multi Resolution SignalDecomposition:the Wavelet Representation[J].IEEE Trnas on PAMI,1989,11(7):674-693
[4]Goutaias,H J A M.Heijmans.MultiresolutionSignal Decomposition Schemes.Part2:Morphological Wavelets[J].IEEE Transactions onImage Processing,2000,9(11):1 877-1 896
[5]段汕,秦前清.具有附益性的形态塔式变换及其应用[J].武汉大学学报(理学版),2004,50(1):74-78
[6]Allan G H,Serar J.Morphological Operators onthe Unit Circle[J].IEEE Transactions on ImageProcessing,2001,10(12):291-233
[7]Gregory B,Anthony V.Wavelet Transforms&Compression of Seismic Data.Tech.Report[R].Mathematical Geophisics Summer School atStanford,1998
[8]Reichel J.Integer Wavelet Transform for EmbeddedLossy to Lossless Image Compression[J].IEEETrans.Image Processing,2001,10(6):383-392
[9]Li Feipeng,Ma Guoru,Qin Qianqing,et al.PriorImportant Band Hyper-spectral Image Compression[C].SPIE Proceedings,Multispectral ImageProcessing and Pattern Recognition,Beijing,2003
[10]Heijmans H J A M,Boutsias J.ConstructingMorphological Wavelets with the Lifting Scheme[C].The Fifth International Conference on PatternRecognition and Information Processing(PRIP’99)Minsk,Belarus,1999
[11]Sweldens W.The Liftin Scheme:a Custom-designConstruction of Biorthogonal Wavelets[J].Appliedand Computational Harmonic Analysis,1996(3):186-200
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