A Fast Barzilai-Borwein Gradient Projection for Sparse Reconstruction Algorithm Based on 3D Modeling: Application to ERT Imaging

Image reconstruction for electrical resistance tomography (ERT) is an ill-posed inverse problem. L<sub>1</sub> regularization is used to solve the inverse problem. An effective method of Barzilai-Borwein gradient projection for sparse reconstruction (GPSR-BB) can resolve the inverse prob...

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Autores principales:	Shouxiao Li, Huaxiang Wang, Tonghai Liu, Ziqiang Cui, Joanna N. Chen, Zihan Xia
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Electrical resistance tomography projection method L₁ regularization method gradient projection for sparse reconstruction Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/1815e09e31da4b06882b344c7fe635e4
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id	oai:doaj.org-article:1815e09e31da4b06882b344c7fe635e4
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spelling	oai:doaj.org-article:1815e09e31da4b06882b344c7fe635e42021-11-20T00:01:10ZA Fast Barzilai-Borwein Gradient Projection for Sparse Reconstruction Algorithm Based on 3D Modeling: Application to ERT Imaging2169-353610.1109/ACCESS.2021.3127695https://doaj.org/article/1815e09e31da4b06882b344c7fe635e42021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9612176/https://doaj.org/toc/2169-3536Image reconstruction for electrical resistance tomography (ERT) is an ill-posed inverse problem. L<sub>1</sub> regularization is used to solve the inverse problem. An effective method of Barzilai-Borwein gradient projection for sparse reconstruction (GPSR-BB) can resolve the inverse problem into bound-constrained quadratic programming and achieve a gradient projection with line search. However, it is computationally expensive to solve the problem when the data dimension is substantial. Hence, a projection method is employed and combined with the GPSR-BB algorithm to improve the real-time performance. The problem can be mainly solved in the Krylov subspace. For comparison, another L<sub>1</sub> regularization GPSR-BB method based on the truncated singular value decomposition is also conducted. Both simulation (with 3D modeling) and experimental results demonstrate the new method’s effectiveness in reducing the computational time and improving the image quality.Shouxiao LiHuaxiang WangTonghai LiuZiqiang CuiJoanna N. ChenZihan XiaIEEEarticleElectrical resistance tomographyprojection methodL₁ regularization methodgradient projection for sparse reconstructionElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 152913-152922 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Electrical resistance tomography projection method L₁ regularization method gradient projection for sparse reconstruction Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Electrical resistance tomography projection method L₁ regularization method gradient projection for sparse reconstruction Electrical engineering. Electronics. Nuclear engineering TK1-9971 Shouxiao Li Huaxiang Wang Tonghai Liu Ziqiang Cui Joanna N. Chen Zihan Xia A Fast Barzilai-Borwein Gradient Projection for Sparse Reconstruction Algorithm Based on 3D Modeling: Application to ERT Imaging
description	Image reconstruction for electrical resistance tomography (ERT) is an ill-posed inverse problem. L<sub>1</sub> regularization is used to solve the inverse problem. An effective method of Barzilai-Borwein gradient projection for sparse reconstruction (GPSR-BB) can resolve the inverse problem into bound-constrained quadratic programming and achieve a gradient projection with line search. However, it is computationally expensive to solve the problem when the data dimension is substantial. Hence, a projection method is employed and combined with the GPSR-BB algorithm to improve the real-time performance. The problem can be mainly solved in the Krylov subspace. For comparison, another L<sub>1</sub> regularization GPSR-BB method based on the truncated singular value decomposition is also conducted. Both simulation (with 3D modeling) and experimental results demonstrate the new method’s effectiveness in reducing the computational time and improving the image quality.
format	article
author	Shouxiao Li Huaxiang Wang Tonghai Liu Ziqiang Cui Joanna N. Chen Zihan Xia
author_facet	Shouxiao Li Huaxiang Wang Tonghai Liu Ziqiang Cui Joanna N. Chen Zihan Xia
author_sort	Shouxiao Li
title	A Fast Barzilai-Borwein Gradient Projection for Sparse Reconstruction Algorithm Based on 3D Modeling: Application to ERT Imaging
title_short	A Fast Barzilai-Borwein Gradient Projection for Sparse Reconstruction Algorithm Based on 3D Modeling: Application to ERT Imaging
title_full	A Fast Barzilai-Borwein Gradient Projection for Sparse Reconstruction Algorithm Based on 3D Modeling: Application to ERT Imaging
title_fullStr	A Fast Barzilai-Borwein Gradient Projection for Sparse Reconstruction Algorithm Based on 3D Modeling: Application to ERT Imaging
title_full_unstemmed	A Fast Barzilai-Borwein Gradient Projection for Sparse Reconstruction Algorithm Based on 3D Modeling: Application to ERT Imaging
title_sort	fast barzilai-borwein gradient projection for sparse reconstruction algorithm based on 3d modeling: application to ert imaging
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/1815e09e31da4b06882b344c7fe635e4
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A Fast Barzilai-Borwein Gradient Projection for Sparse Reconstruction Algorithm Based on 3D Modeling: Application to ERT Imaging

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