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Article: Fast image restoration methods for impulse and Gaussian noises removal

TitleFast image restoration methods for impulse and Gaussian noises removal
Authors
KeywordsDeblurring
Total variation
Impulse noise
Gaussian noise
Denoising
Issue Date2009
Citation
IEEE Signal Processing Letters, 2009, v. 16, n. 6, p. 457-460 How to Cite?
AbstractIn 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 Identifierhttp://hdl.handle.net/10722/276852
ISSN
2023 Impact Factor: 3.2
2023 SCImago Journal Rankings: 1.271
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorHuang, Yu Mei-
dc.contributor.authorNg, Michael K.-
dc.contributor.authorWen, You Wei-
dc.date.accessioned2019-09-18T08:34:51Z-
dc.date.available2019-09-18T08:34:51Z-
dc.date.issued2009-
dc.identifier.citationIEEE Signal Processing Letters, 2009, v. 16, n. 6, p. 457-460-
dc.identifier.issn1070-9908-
dc.identifier.urihttp://hdl.handle.net/10722/276852-
dc.description.abstractIn 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.languageeng-
dc.relation.ispartofIEEE Signal Processing Letters-
dc.subjectDeblurring-
dc.subjectTotal variation-
dc.subjectImpulse noise-
dc.subjectGaussian noise-
dc.subjectDenoising-
dc.titleFast image restoration methods for impulse and Gaussian noises removal-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/LSP.2009.2016835-
dc.identifier.scopuseid_2-s2.0-73849130317-
dc.identifier.volume16-
dc.identifier.issue6-
dc.identifier.spage457-
dc.identifier.epage460-
dc.identifier.isiWOS:000265994300003-
dc.identifier.issnl1070-9908-

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