An Algorithm of l1-Norm and l0-Norm Regularization Algorithm for CT Image Reconstruction from Limited Projection

The l1-norm regularization has attracted attention for image reconstruction in computed tomography. The l0-norm of the gradients of an image provides a measure of the sparsity of gradients of the image. In this paper, we present a new combined l1-norm and l0-norm regularization model for image recon...

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Main Authors: Xiezhang Li, Guocan Feng, Jiehua Zhu
Format: Article
Language:English
Published: Hindawi Limited 2020-01-01
Series:International Journal of Biomedical Imaging
Online Access:http://dx.doi.org/10.1155/2020/8873865
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spelling doaj-e4f704ce4bc943d89b9045ba619c28b82020-11-25T03:11:35ZengHindawi LimitedInternational Journal of Biomedical Imaging1687-41881687-41962020-01-01202010.1155/2020/88738658873865An Algorithm of l1-Norm and l0-Norm Regularization Algorithm for CT Image Reconstruction from Limited ProjectionXiezhang Li0Guocan Feng1Jiehua Zhu2Department of Mathematical Sciences, Georgia Southern University, Statesboro 30460, USASchool of Mathematics, Sun Yat-sen University, Guangzhou 510275, ChinaDepartment of Mathematical Sciences, Georgia Southern University, Statesboro 30460, USAThe l1-norm regularization has attracted attention for image reconstruction in computed tomography. The l0-norm of the gradients of an image provides a measure of the sparsity of gradients of the image. In this paper, we present a new combined l1-norm and l0-norm regularization model for image reconstruction from limited projection data in computed tomography. We also propose an algorithm in the algebraic framework to solve the optimization effectively using the nonmonotone alternating direction algorithm with hard thresholding method. Numerical experiments indicate that this new algorithm makes much improvement by involving l0-norm regularization.http://dx.doi.org/10.1155/2020/8873865
collection DOAJ
language English
format Article
sources DOAJ
author Xiezhang Li
Guocan Feng
Jiehua Zhu
spellingShingle Xiezhang Li
Guocan Feng
Jiehua Zhu
An Algorithm of l1-Norm and l0-Norm Regularization Algorithm for CT Image Reconstruction from Limited Projection
International Journal of Biomedical Imaging
author_facet Xiezhang Li
Guocan Feng
Jiehua Zhu
author_sort Xiezhang Li
title An Algorithm of l1-Norm and l0-Norm Regularization Algorithm for CT Image Reconstruction from Limited Projection
title_short An Algorithm of l1-Norm and l0-Norm Regularization Algorithm for CT Image Reconstruction from Limited Projection
title_full An Algorithm of l1-Norm and l0-Norm Regularization Algorithm for CT Image Reconstruction from Limited Projection
title_fullStr An Algorithm of l1-Norm and l0-Norm Regularization Algorithm for CT Image Reconstruction from Limited Projection
title_full_unstemmed An Algorithm of l1-Norm and l0-Norm Regularization Algorithm for CT Image Reconstruction from Limited Projection
title_sort algorithm of l1-norm and l0-norm regularization algorithm for ct image reconstruction from limited projection
publisher Hindawi Limited
series International Journal of Biomedical Imaging
issn 1687-4188
1687-4196
publishDate 2020-01-01
description The l1-norm regularization has attracted attention for image reconstruction in computed tomography. The l0-norm of the gradients of an image provides a measure of the sparsity of gradients of the image. In this paper, we present a new combined l1-norm and l0-norm regularization model for image reconstruction from limited projection data in computed tomography. We also propose an algorithm in the algebraic framework to solve the optimization effectively using the nonmonotone alternating direction algorithm with hard thresholding method. Numerical experiments indicate that this new algorithm makes much improvement by involving l0-norm regularization.
url http://dx.doi.org/10.1155/2020/8873865
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