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干扰控制K均值序贯泛化二维地震信号去噪

Two-Dimensional Seismic Signal Denoising Based on Controlled Interference K-Means Sequential Generalized Algorithm

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摘要

K均值序贯泛化(SGK)去噪算法在字典更新阶段会引入噪声干扰。为了控制噪声干扰对字典原子的影响, 构建一种干扰控制K均值序贯泛化(C-SGK)地震信号去噪算法。该算法在字典更新阶段通过判断信噪比值与设定阈值间的大小来决定是否更新原子。若信噪比值大于设定阈值, 则顺序更新原子, 反之则不更新原子。对人工合成和实际地震信号的去噪结果表明, 本算法能够很好地控制噪声干扰, 且与传统SGK算法比较发现, 本文算法对地震信号的去噪效果更优。

Abstract

A certain amount of noise would be introduced by a dictionary update step using the K-means sequential generalized (SGK) denoising algorithm. To reduce the effect of noise interference on dictionary atoms, a seismic signal denoising algorithm is proposed based on controlled interference SGK (C-SGK) dictionary learning under a compressive sensing framework. The algorithm compares the signal-to-noise ratio and the threshold set in the dictionary update step, which determines whether to update the atom: the atoms should be sequentially updated only if the signal-to-noise ratio is greater than the threshold. The experimental results of synthesized and real seismic signal denoising in this study indicate that the proposed algorithm can effectively control noise interference. Compared with traditional SGK denoising, the proposed algorithm demonstrates a better denoising effect on seismic signals.

Newport宣传-MKS新实验室计划
补充资料

中图分类号:TN911.72;P631.4

DOI:10.3788/lop56.031501

所属栏目:机器视觉

基金项目:河南省高等学校重点科研项目(17A510007)

收稿日期:2018-06-04

修改稿日期:2018-07-06

网络出版日期:2018-08-15

作者单位    点击查看

冯振杰:安阳师范学院计算机与信息工程学院, 河南 安阳 455000
张欢:河北工业大学电子信息工程学院, 天津 300401
张成:河北工业大学电子信息工程学院, 天津 300401

联系人作者:冯振杰(49909413@qq.com)

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引用该论文

Feng Zhenjie,Zhang Huan,Zhang Cheng. Two-Dimensional Seismic Signal Denoising Based on Controlled Interference K-Means Sequential Generalized Algorithm[J]. Laser & Optoelectronics Progress, 2019, 56(3): 031501

冯振杰,张欢,张成. 干扰控制K均值序贯泛化二维地震信号去噪[J]. 激光与光电子学进展, 2019, 56(3): 031501

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