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- Publisher Website: 10.1016/j.amc.2003.11.017
- Scopus: eid_2-s2.0-9644291756
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Article: Image restoration by cosine transform-based iterative regularization
Title | Image restoration by cosine transform-based iterative regularization |
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Authors | |
Issue Date | 2005 |
Citation | Applied Mathematics and Computation, 2005, v. 160, n. 2, p. 499-515 How to Cite? |
Abstract | We consider an ill-posed deconvolution problem with a noise-contaminated observation, and a known convolution kernel. In this paper, we consider the use of the Neumann boundary condition (corresponding to a reflection of the original scene at the boundary). The resulting blurring matrices are block Toeplitz-plus-Hankel matrices with Toeplitz-plus-Hankel blocks. We study the application of the preconditioned iterative regularization scheme for solving these linear systems, where the blurring matrices are approximated by cosine transform preconditioners. We give a simple approach for finding these preconditioners and show how iterations can be effectively and efficiently regularized for solving ill-posed problems by using the spectral decomposition of the preconditioner. © 2003 Elsevier Inc. All rights reserved. |
Persistent Identifier | http://hdl.handle.net/10722/276657 |
ISSN | 2021 Impact Factor: 4.397 2020 SCImago Journal Rankings: 0.972 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Ng, Michael K. | - |
dc.contributor.author | Kwan, Wilson C. | - |
dc.date.accessioned | 2019-09-18T08:34:16Z | - |
dc.date.available | 2019-09-18T08:34:16Z | - |
dc.date.issued | 2005 | - |
dc.identifier.citation | Applied Mathematics and Computation, 2005, v. 160, n. 2, p. 499-515 | - |
dc.identifier.issn | 0096-3003 | - |
dc.identifier.uri | http://hdl.handle.net/10722/276657 | - |
dc.description.abstract | We consider an ill-posed deconvolution problem with a noise-contaminated observation, and a known convolution kernel. In this paper, we consider the use of the Neumann boundary condition (corresponding to a reflection of the original scene at the boundary). The resulting blurring matrices are block Toeplitz-plus-Hankel matrices with Toeplitz-plus-Hankel blocks. We study the application of the preconditioned iterative regularization scheme for solving these linear systems, where the blurring matrices are approximated by cosine transform preconditioners. We give a simple approach for finding these preconditioners and show how iterations can be effectively and efficiently regularized for solving ill-posed problems by using the spectral decomposition of the preconditioner. © 2003 Elsevier Inc. All rights reserved. | - |
dc.language | eng | - |
dc.relation.ispartof | Applied Mathematics and Computation | - |
dc.title | Image restoration by cosine transform-based iterative regularization | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1016/j.amc.2003.11.017 | - |
dc.identifier.scopus | eid_2-s2.0-9644291756 | - |
dc.identifier.volume | 160 | - |
dc.identifier.issue | 2 | - |
dc.identifier.spage | 499 | - |
dc.identifier.epage | 515 | - |
dc.identifier.isi | WOS:000225345700017 | - |
dc.identifier.issnl | 0096-3003 | - |