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- Publisher Website: 10.1155/ASP/2006/35726
- Scopus: eid_2-s2.0-33645164251
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Article: A fast algorithm for image super-resolution from blurred observations
Title | A fast algorithm for image super-resolution from blurred observations |
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Authors | |
Issue Date | 2006 |
Citation | EURASIP Journal on Applied Signal Processing, 2006, v. 2006, article no. 035726, p. 1-14 How to Cite? |
Abstract | We study the problem of reconstruction of a high-resolution image from several blurred low-resolution image frames. The image frames consist of blurred, decimated, and noisy versions of a high-resolution image. The high-resolution image is modeled as a Markov random field (MRF), and a maximum a posteriori (MAP) estimation technique is used for the restoration. We show that with the periodic boundary condition, a high-resolution image can be restored efficiently by using fast Fourier transforms. We also apply the preconditioned conjugate gradient method to restore high-resolution images in the aperiodic boundary condition. Computer simulations are given to illustrate the effectiveness of the proposed approach. Copyright © 2006 Hindawi Publishing Corporation. All rights reserved. |
Persistent Identifier | http://hdl.handle.net/10722/276790 |
ISSN | |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Bose, Nirmal K. | - |
dc.contributor.author | Ng, Michael K. | - |
dc.contributor.author | Yau, Andy C. | - |
dc.date.accessioned | 2019-09-18T08:34:40Z | - |
dc.date.available | 2019-09-18T08:34:40Z | - |
dc.date.issued | 2006 | - |
dc.identifier.citation | EURASIP Journal on Applied Signal Processing, 2006, v. 2006, article no. 035726, p. 1-14 | - |
dc.identifier.issn | 1110-8657 | - |
dc.identifier.uri | http://hdl.handle.net/10722/276790 | - |
dc.description.abstract | We study the problem of reconstruction of a high-resolution image from several blurred low-resolution image frames. The image frames consist of blurred, decimated, and noisy versions of a high-resolution image. The high-resolution image is modeled as a Markov random field (MRF), and a maximum a posteriori (MAP) estimation technique is used for the restoration. We show that with the periodic boundary condition, a high-resolution image can be restored efficiently by using fast Fourier transforms. We also apply the preconditioned conjugate gradient method to restore high-resolution images in the aperiodic boundary condition. Computer simulations are given to illustrate the effectiveness of the proposed approach. Copyright © 2006 Hindawi Publishing Corporation. All rights reserved. | - |
dc.language | eng | - |
dc.relation.ispartof | EURASIP Journal on Applied Signal Processing | - |
dc.title | A fast algorithm for image super-resolution from blurred observations | - |
dc.type | Article | - |
dc.description.nature | link_to_OA_fulltext | - |
dc.identifier.doi | 10.1155/ASP/2006/35726 | - |
dc.identifier.scopus | eid_2-s2.0-33645164251 | - |
dc.identifier.volume | 2006 | - |
dc.identifier.spage | article no. 035726, p. 1 | - |
dc.identifier.epage | article no. 035726, p. 14 | - |
dc.identifier.isi | WOS:000242065400001 | - |
dc.identifier.issnl | 1110-8657 | - |