系统仿真学报 ›› 2017, Vol. 29 ›› Issue (8): 1851-1858.doi: 10.16182/j.issn1004731x.joss.201708028

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基于广义正则化的ECT图像重建算法

马敏, 郭琪, 闫超奇   

  1. 中国民航大学电子信息与自动化学院,天津 300300
  • 收稿日期:2016-11-15 发布日期:2020-06-01
  • 作者简介:马敏(1971-),女,安徽六安,博士,教授,研究方向为电学层析成像算法;郭琪(1990-),男,山西吕梁,硕士生,研究方向为电学层析成像算法;闫超奇(1992-),男,河南新乡,硕士生,研究方向为电学成像。
  • 基金资助:
    国家自然科学基金(61401466),中国民航大学科研启动基金(2013QD01S)

ECT Image Reconstruction Algorithm Based on Generalized Regularization

Ma Min, Guo Qi, Yan Chaoqi   

  1. College of Electronic Information and Automation, Civil Aviation University of China, Tianjin 300300, China
  • Received:2016-11-15 Published:2020-06-01

摘要: 针对电容层析成像(Electrical Capacitance Tomography,ECT)系统图像重建过程中Tiknonov正则化引起的解的过度光滑和奇异值分解算法引起的数值不稳定,提出了一种更为广义的正则化算法。利用正定矩阵对正则化目标函数的惩罚相修正,使其可以对包含非光滑性信息的图像进行更准确重构,在目标函数求解过程中引入对角权值矩阵,对基于l2范数的数据项改进,通过重建图像质量、图像相对误差、图像相对系数等指标对3种算法进行评估。实验结果表明,广义正则化算法相比Tiknonov正则化算法和奇异值分解算法,可以对物场中不同介质有效区分,避免图像的过度平滑,分辨率较高,重建质量较好。

关键词: 电容层析成像, 过度光滑, 正定矩阵, 广义正则化算法, 图像重建

Abstract: Aiming at the numerical instability caused by the singular value decomposition algorithm and the over-smooth caused by the Tiknonov regularization in the image reconstruction of electrical capacitance tomography (ECT) system, a more generalized regularization algorithm was proposed. The penalty phase of the regularized objective function was modified by the positive definite matrix so that it could reconstruct the image with non smooth information, In the process of solving the objective function, the diagonal weight matrix was introduced, and the data items based on l2-norm were improved. By comparing the image quality, the relative error of the image and the relative coefficient of the image, the three algorithms were evaluated. Resultsshow that the generalized regularization algorithm compared to Tiknonov regularization algorithm and singular value decomposition algorithm, can distinguish the substance field in different medium effectively and obtain high quality reconstruction images while avoiding over-smooth.

Key words: electrical capacitance tomography, over-smooth, positive definite matrix, generalized regularization algorithm, image reconstruction

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