东北大学学报（自然科学版）

东北大学学报:自然科学版 ›› 2015, Vol. 36 ›› Issue (12): 1687-1690.DOI: 10.12068/j.issn.1005-3026.2015.12.004

• 信息与控制 • 上一篇    下一篇

基于压缩感知的MIT图像重建方法

王静文， 王旭   

  1. (东北大学 信息科学与工程学院， 辽宁 沈阳110819)
  • 收稿日期:2014-11-23 修回日期:2014-11-23 出版日期:2015-12-15 发布日期:2015-12-07
  • 通讯作者: 王静文
  • 作者简介:王静文 (1988-)，女，辽宁锦州人，东北大学博士研究生; 王旭(1956-)，男，辽宁沈阳人，东北大学教授，博士生导师.
  • 基金资助:
    中央高校基本科研业务费专项资金资助项目(N130404004).

Image Reconstruction Method Based on Compressed Sensing for Magnetic Induction Tomography

WANG Jing-wen， WANG Xu   

  1. School of Information Science & Engineering， Northeastern University， Shenyang 110819， China.
  • Received:2014-11-23 Revised:2014-11-23 Online:2015-12-15 Published:2015-12-07
  • Contact: WANG Jing-wen
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摘要： 针对目前磁感应成像技术(MIT)的图像重建质量存在精度较低的问题，提出了一种基于压缩感知原MIT图像重建方法.将MIT系统电压数据的采集过程视为压缩感知的线性测量过程，通过对灵敏度矩阵进行补零拓展和行向量随机重组操作重新设计了测量矩阵；采集到的电压向量也用相同的方式处理，作为压缩感知的测量信号.然后利用压缩感知信号重构算法恢复原始信号.最后进行了仿真实验，实验结果表明，利用本方法获得的重建图像误差和相关系数比传统图像重建算法要好.由此可见，这是一种精度较高的MIT图像重建方法.

关键词: 磁感应成像, 压缩感知, 图像重建, 图像误差, 相关系数

Abstract: To improve image reconstruction quality of magnetic induction tomography (MIT)， a new MIT image reconstruction method based on compressed sensing was put forward. Here the voltage collection process of MIT system was regarded as linear measurement process of compressed sensing， the measurement matrix was designed by zero expansion of the sensitivity matrix and its row vectors random reconstruction， and the measurement voltage vector expanded by the same way was regarded as measurement signals of compressed sensing. The original signal was recovered by signal reconstruction method of compressed sensing. Finally， the simulation experiments were performed. The experimental results indicated that the average image reconstruction error and the average correlation coefficient obtained by the method are better than corresponding indicators obtained by the traditional reconstruction image algorithm. So it is a kind of MIT image reconstruction method with high accuracy.

Key words: magnetic induction tomography(MIT), compressed sensing, image reconstruction, image error, correlation coefficient

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