摘要
针对电容层析成像图像重构Tikhonov正则参数的选取问题,提出利用Morozov偏差原理确定正则参数,使其选取与初始数据的观测误差相匹配,并提出三阶收敛算法与双参数模型相结合的混合算法,使其选取更加快速、合理.数值实验表明:三阶混合算法优于典型的Newton方法;正则参数的选取影响重构图像的精度和速度;对于各种设定流型,本文提出的混合算法重构图像速度更快,重建图像质量更高.
To solve the selection problem of Tikhonov regularization parameter in electrical capacitance tomography,A method is proposed to get an optimal regularization parameter using Morozov discrepancy principle,which make the（output） error due to regularization equals the error level in the data.To get an optimal regularization parameter rapidly and reasonably,a hybrid algorithm by combining three-order convergence algorithm and two parameter model is proposed.Numerical experimental results show that regularization parameter selection affects both the reconstruction speed and quality;the proposed hybrid algorithm has high image reconstruction speed and high accuracy for different flow patterns.
出处
《电子学报》
EI
CAS
CSCD
北大核心
2012年第3期500-504,共5页
Acta Electronica Sinica
基金
河北省自然科学基金资助项目(No.E2007000048)
关键词
电容层析成像
图像重构
双参数模型
三阶算法
Morozov偏差方程
混合算法
electrical capacitance tomography
image reconstruction
two parameter model
three order algorithm
Morozov discrepancy equation
hybrid algorithm
