An Image Reconstruction Algorithm for ECT Using Enhanced Model and Sparsity Regularization

被引：0
|
作者：
Yang, Yunjie [1 ]
Peng, Lihui [1 ]
机构：
[1] Tsinghua Univ, Dept Automat, Tsinghua Natl Lab Informat Sci & Technol, Beijing 100084, Peoples R China
来源：
2013 IEEE INTERNATIONAL CONFERENCE ON IMAGING SYSTEMS AND TECHNIQUES (IST 2013) | 2013年
关键词：
image reconstruction; electrical capacitance tomography; enhanced linear model; wavelet basis; ELECTRICAL CAPACITANCE TOMOGRAPHY; DESIGN;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
An image reconstruction algorithm for electrical capacitance tomography (ECT) using enhanced linear model and sparsity regularization (EMSR) is proposed in this paper. Compared to the traditional ECT linear model, the enhanced linear model takes the nonlinear effect of different capacitance groups and the sensitivity error into account. In addition, the sparsity of permittivity distributions under wavelet basis is investigated and utilized as the regularization term. The proposed algorithm using enhanced model and sparsity regularization is noted as EMSR and the performance is verified by using simulation data and experiment data. Both the simulation and experiment results indicate the potentiality of this method.
引用
收藏
页码：35 / 39
页数：5
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