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- Publisher Website: 10.1016/S0024-3795(00)00115-4
- Scopus: eid_2-s2.0-0034415725
- WOS: WOS:000089045600016
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Article: A new approach to constrained total least squares image restoration
Title | A new approach to constrained total least squares image restoration |
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Authors | |
Keywords | Regularization Neumann boundary condition Deconvolution Constrained total least squares Toeplitz matrix |
Issue Date | 2000 |
Citation | Linear Algebra and Its Applications, 2000, v. 316, n. 1-3, p. 237-258 How to Cite? |
Abstract | Recently there has been a growing interest and progress in using total least squares (TLS) methods for solving blind deconvolution problems arising in image restoration. Here, the true image is to be estimated using only partial information about the blurring operator, or point spread function (PSF), which is subject to error and noise. In this paper, we present a new iterative, regularized, and constrained TLS image restoration algorithm. Neumann boundary conditions are used to reduce the boundary artifacts that normally occur in restoration processes. Preliminary numerical tests are reported on some simulated optical imaging problems in order to illustrate the effectiveness of the approach, as well as the fast convergence of our iterative scheme. © 2000 Elsevier Science Inc. |
Persistent Identifier | http://hdl.handle.net/10722/276721 |
ISSN | 2023 Impact Factor: 1.0 2023 SCImago Journal Rankings: 0.837 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Ng, Michael K. | - |
dc.contributor.author | Plemmons, Robert J. | - |
dc.contributor.author | Pimentel, Felipe | - |
dc.date.accessioned | 2019-09-18T08:34:27Z | - |
dc.date.available | 2019-09-18T08:34:27Z | - |
dc.date.issued | 2000 | - |
dc.identifier.citation | Linear Algebra and Its Applications, 2000, v. 316, n. 1-3, p. 237-258 | - |
dc.identifier.issn | 0024-3795 | - |
dc.identifier.uri | http://hdl.handle.net/10722/276721 | - |
dc.description.abstract | Recently there has been a growing interest and progress in using total least squares (TLS) methods for solving blind deconvolution problems arising in image restoration. Here, the true image is to be estimated using only partial information about the blurring operator, or point spread function (PSF), which is subject to error and noise. In this paper, we present a new iterative, regularized, and constrained TLS image restoration algorithm. Neumann boundary conditions are used to reduce the boundary artifacts that normally occur in restoration processes. Preliminary numerical tests are reported on some simulated optical imaging problems in order to illustrate the effectiveness of the approach, as well as the fast convergence of our iterative scheme. © 2000 Elsevier Science Inc. | - |
dc.language | eng | - |
dc.relation.ispartof | Linear Algebra and Its Applications | - |
dc.subject | Regularization | - |
dc.subject | Neumann boundary condition | - |
dc.subject | Deconvolution | - |
dc.subject | Constrained total least squares | - |
dc.subject | Toeplitz matrix | - |
dc.title | A new approach to constrained total least squares image restoration | - |
dc.type | Article | - |
dc.description.nature | link_to_OA_fulltext | - |
dc.identifier.doi | 10.1016/S0024-3795(00)00115-4 | - |
dc.identifier.scopus | eid_2-s2.0-0034415725 | - |
dc.identifier.volume | 316 | - |
dc.identifier.issue | 1-3 | - |
dc.identifier.spage | 237 | - |
dc.identifier.epage | 258 | - |
dc.identifier.isi | WOS:000089045600016 | - |
dc.identifier.issnl | 0024-3795 | - |