| 基于Curvelet变换阈值法的地震数据插值和去噪 |
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| 引用本文： | 薛念,周黎霞,尹忠科.基于Curvelet变换阈值法的地震数据插值和去噪[J].交通运输工程与信息学报,2011,9(2):86-91. |
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| 作者姓名： | 薛念 周黎霞 尹忠科 |
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| 作者单位： | 1. 西南交通大学,信息科学与技术学院,成都,610031
2. 中国石油塔里木油田分公司,新疆,库尔勒841000 |
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| 基金项目： | 国家科技重大专项子课题(2008ZX05046); 国家自然科学基金(60772084)资助 |
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| 摘 要： | 成功的信号分离和去噪依赖于所用的变换能否足够稀疏地表达该类信号.事实上,信号在某变换域的系数越稀疏,阈值去噪的效果也就越好.Curvelet变换是一种非自适应的多尺度.多方向性变换,地震数据在Curvelet域有着几乎最优的稀疏表达.最近的研究表明,Curvelet阈值能够得到比小波阈值更好的随机噪声抑制效果,更高的提...
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| 关 键 词： | Curvelet变换 阈值去噪 地震数据插值 |
Curvelet Thresholding for Seismic Data Denoising and Interpolating |
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| XUE Nian,ZHOU Li-xia,YIN Zhong-ke.Curvelet Thresholding for Seismic Data Denoising and Interpolating[J].Journal of Transportation Engineering and Information,2011,9(2):86-91. |
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| Authors: | XUE Nian ZHOU Li-xia YIN Zhong-ke |
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| Institution: | XUE Nian1 ZHOU Li-xia2 YIN Zhong-ke1 1.School of Information Science & Technology,Southwest Jiaotong University,Chengdu 610031,China 2.Petrochina Tarim Oil Field,Korla 841000,Xinjiang,China |
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| Abstract: | The success of signal denoising and separating depends largely on the ability of a transform to sparsely represent a particular type of a signal.In fact,the sparser the transformation is,the better denoising result will be achieved from the coefficient shrinkage.Curvelet transform is a multi-scale directional transform,which allows an almost optimal non-adaptive sparse representation for seismic data.Recent research has shown that the method of curvelet thresholding could suppress the random noise more effe... |
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| Keywords: | Curvelet transform thresholding denoising seismic data interpolation |
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