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- Publisher Website: 10.1109/LSP.2009.2016835
- Scopus: eid_2-s2.0-73849130317
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Article: Fast image restoration methods for impulse and Gaussian noises removal
Title | Fast image restoration methods for impulse and Gaussian noises removal |
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Authors | |
Keywords | Deblurring Total variation Impulse noise Gaussian noise Denoising |
Issue Date | 2009 |
Citation | IEEE Signal Processing Letters, 2009, v. 16, n. 6, p. 457-460 How to Cite? |
Abstract | In this paper, we study the restoration of blurred images corrupted by impulse noise or mixed impulse plus Gaussian noises. In the proposed method, we use the modified total variation minimization scheme to regularize the deblurred image and fill in suitable values for noisy image pixels where these are detected by median-type filters. An alternating minimization algorithm is employed to solve the proposed total variation minimization problem. Our experimental results show the proposed algorithm is very efficient and the quality of restored images by the proposed method is competitive with those restored by the existing variational image restoration methods. © 2009 IEEE. |
Persistent Identifier | http://hdl.handle.net/10722/276852 |
ISSN | 2023 Impact Factor: 3.2 2023 SCImago Journal Rankings: 1.271 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Huang, Yu Mei | - |
dc.contributor.author | Ng, Michael K. | - |
dc.contributor.author | Wen, You Wei | - |
dc.date.accessioned | 2019-09-18T08:34:51Z | - |
dc.date.available | 2019-09-18T08:34:51Z | - |
dc.date.issued | 2009 | - |
dc.identifier.citation | IEEE Signal Processing Letters, 2009, v. 16, n. 6, p. 457-460 | - |
dc.identifier.issn | 1070-9908 | - |
dc.identifier.uri | http://hdl.handle.net/10722/276852 | - |
dc.description.abstract | In this paper, we study the restoration of blurred images corrupted by impulse noise or mixed impulse plus Gaussian noises. In the proposed method, we use the modified total variation minimization scheme to regularize the deblurred image and fill in suitable values for noisy image pixels where these are detected by median-type filters. An alternating minimization algorithm is employed to solve the proposed total variation minimization problem. Our experimental results show the proposed algorithm is very efficient and the quality of restored images by the proposed method is competitive with those restored by the existing variational image restoration methods. © 2009 IEEE. | - |
dc.language | eng | - |
dc.relation.ispartof | IEEE Signal Processing Letters | - |
dc.subject | Deblurring | - |
dc.subject | Total variation | - |
dc.subject | Impulse noise | - |
dc.subject | Gaussian noise | - |
dc.subject | Denoising | - |
dc.title | Fast image restoration methods for impulse and Gaussian noises removal | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/LSP.2009.2016835 | - |
dc.identifier.scopus | eid_2-s2.0-73849130317 | - |
dc.identifier.volume | 16 | - |
dc.identifier.issue | 6 | - |
dc.identifier.spage | 457 | - |
dc.identifier.epage | 460 | - |
dc.identifier.isi | WOS:000265994300003 | - |
dc.identifier.issnl | 1070-9908 | - |