Prior Image Induced Regularization Method for Electrical Capacitance Tomography

The image reconstruction is a crucial step in the electrical capacitance tomography. This paper presents a new methodology for improving the reconstruction accuracy. The prior image induced regularization from the deep convolutional extreme learning machine (DCELM) is introduced, which is integrated...

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Main Authors: Pan Chu, Jing Lei, Qibin Liu
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8572696/
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author Pan Chu
Jing Lei
Qibin Liu
author_facet Pan Chu
Jing Lei
Qibin Liu
author_sort Pan Chu
collection DOAJ
description The image reconstruction is a crucial step in the electrical capacitance tomography. This paper presents a new methodology for improving the reconstruction accuracy. The prior image induced regularization from the deep convolutional extreme learning machine (DCELM) is introduced, which is integrated with the domain knowledge related to imaging targets to form a more effective mathematical model for reconstruction. A new numerical scheme is developed to train the DCELM more effectively. The fast iterative shrinkage-thresholding method is embedded into the alternating direction method of multipliers (ADMM) to form a new solver for the proposed imaging model. Extensive validations are implemented to evaluate the proposed imaging method. The numerical results demonstrate that the proposed imaging technique outperforms the state-of-the-art reconstruction methods and produces better reconstructions.
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spelling doaj.art-59459c0e34934d02b4a7afea24215a632022-12-21T19:56:44ZengIEEEIEEE Access2169-35362019-01-0172490250110.1109/ACCESS.2018.28862398572696Prior Image Induced Regularization Method for Electrical Capacitance TomographyPan Chu0https://orcid.org/0000-0002-3487-2793Jing Lei1Qibin Liu2China Energy Engineering Group, Guangdong Electric Power Design Institute Co., Ltd., Guangzhou, ChinaSchool of Energy, Power and Mechanical Engineering, North China Electric Power University, Beijing, ChinaChinese Academy of Sciences, Institute of Engineering Thermophysics, Beijing, ChinaThe image reconstruction is a crucial step in the electrical capacitance tomography. This paper presents a new methodology for improving the reconstruction accuracy. The prior image induced regularization from the deep convolutional extreme learning machine (DCELM) is introduced, which is integrated with the domain knowledge related to imaging targets to form a more effective mathematical model for reconstruction. A new numerical scheme is developed to train the DCELM more effectively. The fast iterative shrinkage-thresholding method is embedded into the alternating direction method of multipliers (ADMM) to form a new solver for the proposed imaging model. Extensive validations are implemented to evaluate the proposed imaging method. The numerical results demonstrate that the proposed imaging technique outperforms the state-of-the-art reconstruction methods and produces better reconstructions.https://ieeexplore.ieee.org/document/8572696/Prior image induced regularizationimage reconstructioninverse problemdeep convolutional extreme learning machineiterative imaging methodelectrical capacitance tomography
spellingShingle Pan Chu
Jing Lei
Qibin Liu
Prior Image Induced Regularization Method for Electrical Capacitance Tomography
IEEE Access
Prior image induced regularization
image reconstruction
inverse problem
deep convolutional extreme learning machine
iterative imaging method
electrical capacitance tomography
title Prior Image Induced Regularization Method for Electrical Capacitance Tomography
title_full Prior Image Induced Regularization Method for Electrical Capacitance Tomography
title_fullStr Prior Image Induced Regularization Method for Electrical Capacitance Tomography
title_full_unstemmed Prior Image Induced Regularization Method for Electrical Capacitance Tomography
title_short Prior Image Induced Regularization Method for Electrical Capacitance Tomography
title_sort prior image induced regularization method for electrical capacitance tomography
topic Prior image induced regularization
image reconstruction
inverse problem
deep convolutional extreme learning machine
iterative imaging method
electrical capacitance tomography
url https://ieeexplore.ieee.org/document/8572696/
work_keys_str_mv AT panchu priorimageinducedregularizationmethodforelectricalcapacitancetomography
AT jinglei priorimageinducedregularizationmethodforelectricalcapacitancetomography
AT qibinliu priorimageinducedregularizationmethodforelectricalcapacitancetomography