Steerable Pyramid分解地震随机噪声衰减——基于局部Laplace先验概率密度模型  

Noise decaying of seismic data by Steerable Pyramid decomposition based on Laplace prior

作　　者：林春[1] 王绪本[1] 刘力辉[1,2] 

机构地区：[1]成都理工大学地球探测与信息技术教育部重点实验室,成都610059 [2]北京诺克斯达石油科技有限公司,北京100192

出　　处：《计算机工程与应用》2012年第2期222-226,共5页Computer Engineering and Applications

基　　金：国家科技重大专项子题地震相分析及相控反演技术(No.2008ZX05005-005-008HZ);川庆公司科学技术研究项目

摘　　要：简单介绍了具有多尺度与多方向性特点的Steerable Pyramid分解和重构的基本原理。采用softLMAP阈值将其应用于地震数据随机噪声衰减中,进行了仿真计算和实际资料的处理并与自适应BayesShrink阈值及小波域softLMAP阈值去噪进行比较。结果证明利用Steerable Pyramid分解softLMAP阈值能比较彻底地去掉噪声,去噪后的图像边缘保持良好,滤除噪声同时还保留了有效部分,去噪效果良好,且易于实现,在地震资料处理中具有一定的可行性和应用前景。The basic principle of decomposition and construction of Steerable Pyramid,which has multi-scale and multi-direction characteristics is introduced.It is applied in the random noise decaying of seismic data based on softLMAP threshold,and emulation and real data processing are given.The effect of noise decaying of Steerable Pyramid decomposition based on softLMAP threshold is compared with that of adaptive BayesShrink threshold and wavelet transform based on softLMAP threshold.The results prove that Steerable Pyramid transform based on softLMAP threshold can relatively completely remove the noise while the edge of picture keeps well and the detail part also keeps at the same time.The result of noise decaying is good and easy to realize,so that Steerable Pyramid decomposition has the feasibility and prospect in the seismic data process.

关 键 词：Steerable PYRAMID softLMAP 自适应BayesShrink 小波分解 随机噪声 

分 类 号：TN911.7[电子电信—通信与信息系统]