首页 | 本学科首页   官方微博 | 高级检索  
     

超声逆散射成像方法研究
引用本文:张培,王浩全,李嫒,吕晶晶.超声逆散射成像方法研究[J].计算机工程,2012,38(4):257-259.
作者姓名:张培  王浩全  李嫒  吕晶晶
作者单位:中北大学仪器科学与动态测试教育部重点实验室,太原,030051
基金项目:山西省自然科学基金资助项目(2011011015-2);中北大学仪器科学与动态测试技术教育部重点实验室青年基金资助项目
摘    要:在研究奇异值分解、最小二乘法的基础上,采用空间域方法研究超声逆散射成像问题。通过脉冲基和点匹配的方法将泛函方程转换为代数方程,运用迭代算法解决方程的非线性问题。利用Picard准则判断方程的不适定程度,并采用均值处理和截断奇异值分解正则化2种方法对方程进行求解。实验结果证明,该方法可以较好地滤除噪声,提高重建图像的质量和可信度,减少迭代过程中的计算量。

关 键 词:逆散射  空间域  矩量法  Born迭代  奇异值分解  离散正则化
收稿时间:2011-07-28

Research on Ultrasound Inverse Scattering Imaging Method
ZHANG Pei , WANG Hao-quan , LI Yuan , LV Jing-jing.Research on Ultrasound Inverse Scattering Imaging Method[J].Computer Engineering,2012,38(4):257-259.
Authors:ZHANG Pei  WANG Hao-quan  LI Yuan  LV Jing-jing
Affiliation:(Key Lab on Instrumentation Science & Dynamic Measurement, Ministry of Education North University of China, Taiyuan 030051, China)
Abstract:Ultrasound inverse scattering imaging is studied by a method of spatial domain based on Singular Value Decomposition(SVD) and least squares solution. By converting the functional equation to algebraic equation with the approach of pulse basis and pointed-match, nonlinear problems are solved by iterative algorithm. The extent of ill-posedness can be determined by Picard theory and the equations can be solved by two kinds of methods of average handling and truncated singular value decomposition. Experimental results illustrate that solving ill-posed equations with appropriate regularization parameter can filter out the noise better and improve the quality of the reconstructed image and credibility, and also can reduce the amount of computation in the iterative process.
Keywords:inverse scattering  spatial domain  moment method  Born iteration  Singular Value Decomposition(SVD)  discrete regularization
本文献已被 CNKI 维普 万方数据 等数据库收录!
点击此处可从《计算机工程》浏览原始摘要信息
点击此处可从《计算机工程》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号