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- Publisher Website: 10.1137/090748421
- Scopus: eid_2-s2.0-78651594680
- WOS: WOS:000278101500001
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Article: Multiplicative noise removal with spatially varying regularization parameters
Title | Multiplicative noise removal with spatially varying regularization parameters |
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Authors | |
Keywords | Textures Total variation Spatially varying regularization parameters Multiplicative noise |
Issue Date | 2010 |
Citation | SIAM Journal on Imaging Sciences, 2010, v. 3, n. 1, p. 1-20 How to Cite? |
Abstract | The Aubert-Aujol (AA) model is a variational method for multiplicative noise removal. In this paper, we study some basic properties of the regularization parameter in the AA model. We develop a method for automatically choosing the regularization parameter in the multiplicative noise removal process. In particular, we employ spatially varying regularization parameters in the AA model in order to restore more texture details of the denoised image. Experimental results are presented to demonstrate that the spatially varying regularization parameters method can obtain better denoised images than the other tested multiplicative noise removal methods. © 2010 Society for Industrial and Applied Mathematics. |
Persistent Identifier | http://hdl.handle.net/10722/276887 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Li, Fang | - |
dc.contributor.author | Ng, Michael K. | - |
dc.contributor.author | Shen, Chaomin | - |
dc.date.accessioned | 2019-09-18T08:34:57Z | - |
dc.date.available | 2019-09-18T08:34:57Z | - |
dc.date.issued | 2010 | - |
dc.identifier.citation | SIAM Journal on Imaging Sciences, 2010, v. 3, n. 1, p. 1-20 | - |
dc.identifier.uri | http://hdl.handle.net/10722/276887 | - |
dc.description.abstract | The Aubert-Aujol (AA) model is a variational method for multiplicative noise removal. In this paper, we study some basic properties of the regularization parameter in the AA model. We develop a method for automatically choosing the regularization parameter in the multiplicative noise removal process. In particular, we employ spatially varying regularization parameters in the AA model in order to restore more texture details of the denoised image. Experimental results are presented to demonstrate that the spatially varying regularization parameters method can obtain better denoised images than the other tested multiplicative noise removal methods. © 2010 Society for Industrial and Applied Mathematics. | - |
dc.language | eng | - |
dc.relation.ispartof | SIAM Journal on Imaging Sciences | - |
dc.subject | Textures | - |
dc.subject | Total variation | - |
dc.subject | Spatially varying regularization parameters | - |
dc.subject | Multiplicative noise | - |
dc.title | Multiplicative noise removal with spatially varying regularization parameters | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1137/090748421 | - |
dc.identifier.scopus | eid_2-s2.0-78651594680 | - |
dc.identifier.volume | 3 | - |
dc.identifier.issue | 1 | - |
dc.identifier.spage | 1 | - |
dc.identifier.epage | 20 | - |
dc.identifier.eissn | 1936-4954 | - |
dc.identifier.isi | WOS:000278101500001 | - |
dc.identifier.issnl | 1936-4954 | - |