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

英文篇名：Noise decaying of seismic data by Steerable Pyramid decomposition based on Laplace prior
中文刊名：计算机工程与应用
英文刊名：Computer Engineering and Applications
作者：林春 ; 王绪本 ; 刘力辉
英文作者：LIN Chun1 ; WANG Xuben1 ; LIU Lihui1 ; 2 1.Chengdu University of Technology KLGIT ; Chengdu 610059 ; China 2.Chinarockstar Petroleum Science and Technology Ltd ; Beijing 100192 ; China
中文关键词：Steerable Pyramid ; softLMAP ; 自适应BayesShrink ; 小波分解 ; 随机噪声
英文关键词：Steerable Pyramid ; softLMAP ; adaptive BayesShrink ; wavelet transform ; random noise
出版日期：2012-01-11
机构：成都理工大学地球探测与信息技术教育部重点实验室;北京诺克斯达石油科技有限公司;
年：2012
期：02
出版单位：计算机工程与应用

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.

引文

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