Restoring Poissonian Images by a Combined First-Order and Second-Order Variation Approach
The restoration of blurred images corrupted by Poisson noise is an important topic in imaging science. The problem has recently received considerable attention in recent years. In this paper, we propose a combined first-order and second-order variation model to restore blurred images corrupted by Po...
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Format: | Article |
Language: | English |
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Wiley
2013-01-01
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Series: | Journal of Mathematics |
Online Access: | http://dx.doi.org/10.1155/2013/274573 |
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author | Le Jiang Jin Huang Xiao-Guang Lv Jun Liu |
author_facet | Le Jiang Jin Huang Xiao-Guang Lv Jun Liu |
author_sort | Le Jiang |
collection | DOAJ |
description | The restoration of blurred images corrupted by Poisson noise is an important topic in imaging science. The problem has recently received considerable attention in recent years. In this paper, we propose a combined first-order and second-order variation model to restore blurred images corrupted by Poisson noise. Our model can substantially reduce the staircase effect, while preserving edges in the restored images, since it combines advantages of the first-order and second-order total variation. We study the issues of existence and uniqueness of a minimizer for this variational model. Moreover, we employ a gradient descent method to solve the associated Euler-Lagrange equation. Numerical results demonstrate the validity and efficiency of the proposed method for
Poisson noise removal problem. |
format | Article |
id | doaj-art-fa32c4f6b83645298b859f35742a793f |
institution | Kabale University |
issn | 2314-4629 2314-4785 |
language | English |
publishDate | 2013-01-01 |
publisher | Wiley |
record_format | Article |
series | Journal of Mathematics |
spelling | doaj-art-fa32c4f6b83645298b859f35742a793f2025-02-03T01:27:17ZengWileyJournal of Mathematics2314-46292314-47852013-01-01201310.1155/2013/274573274573Restoring Poissonian Images by a Combined First-Order and Second-Order Variation ApproachLe Jiang0Jin Huang1Xiao-Guang Lv2Jun Liu3School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan 610054, ChinaSchool of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan 610054, ChinaSchool of Science, Huaihai Institute of Technology, Lianyungang, Jiangsu 222005, ChinaSchool of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan 610054, ChinaThe restoration of blurred images corrupted by Poisson noise is an important topic in imaging science. The problem has recently received considerable attention in recent years. In this paper, we propose a combined first-order and second-order variation model to restore blurred images corrupted by Poisson noise. Our model can substantially reduce the staircase effect, while preserving edges in the restored images, since it combines advantages of the first-order and second-order total variation. We study the issues of existence and uniqueness of a minimizer for this variational model. Moreover, we employ a gradient descent method to solve the associated Euler-Lagrange equation. Numerical results demonstrate the validity and efficiency of the proposed method for Poisson noise removal problem.http://dx.doi.org/10.1155/2013/274573 |
spellingShingle | Le Jiang Jin Huang Xiao-Guang Lv Jun Liu Restoring Poissonian Images by a Combined First-Order and Second-Order Variation Approach Journal of Mathematics |
title | Restoring Poissonian Images by a Combined First-Order and Second-Order Variation Approach |
title_full | Restoring Poissonian Images by a Combined First-Order and Second-Order Variation Approach |
title_fullStr | Restoring Poissonian Images by a Combined First-Order and Second-Order Variation Approach |
title_full_unstemmed | Restoring Poissonian Images by a Combined First-Order and Second-Order Variation Approach |
title_short | Restoring Poissonian Images by a Combined First-Order and Second-Order Variation Approach |
title_sort | restoring poissonian images by a combined first order and second order variation approach |
url | http://dx.doi.org/10.1155/2013/274573 |
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