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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPEW34M/45ALTQ2
Repositorysid.inpe.br/sibgrapi/2021/08.23.19.39
Last Update2021:08.23.19.39.23 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2021/08.23.19.39.23
Metadata Last Update2022:06.14.00.00.16 (UTC) administrator
DOI10.1109/SIBGRAPI54419.2021.00029
Citation KeyLevada:2021:NoMeFi
TitleNon-local medians filter for joint Gaussian and impulsive image denoising
FormatOn-line
Year2021
Access Date2022, Dec. 07
Number of Files1
Size3267 KiB
2. Context
AuthorLevada, Alexandre L. M.
AffiliationComputing Department, Federal University of São Carlos
EditorPaiva, Afonso
Menotti, David
Baranoski, Gladimir V. G.
Proença, Hugo Pedro
Junior, Antonio Lopes Apolinario
Papa, João Paulo
Pagliosa, Paulo
dos Santos, Thiago Oliveira
e Sá, Asla Medeiros
da Silveira, Thiago Lopes Trugillo
Brazil, Emilio Vital
Ponti, Moacir A.
Fernandes, Leandro A. F.
Avila, Sandra
e-Mail Addressalexandre.levada@ufscar.br
Conference NameConference on Graphics, Patterns and Images, 34 (SIBGRAPI)
Conference LocationGramado, RS, Brazil (virtual)
Date18-22 Oct. 2021
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2021-08-23 19:39:23 :: alexandre.levada@ufscar.br -> administrator ::
2022-03-02 00:54:15 :: administrator -> menottid@gmail.com :: 2021
2022-03-02 13:29:55 :: menottid@gmail.com -> administrator :: 2021
2022-06-14 00:00:16 :: administrator -> :: 2021
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
KeywordsImage denoising
Non-local Medians
KL-divergence
impulsive noise
AbstractImage denoising concerns with the development of filters to remove or attenuate random perturbations in the observed data, but at the same time, preserving most of edges and fine details in the scene. One problem with joint additive Gaussian and impulsive noise degradation is that they are spread over all frequencies of the signal. Hence, the most effective filters for this kind of noise are implemented in the spatial domain. In this paper, we proposed a Non-Local Medians filter that combine the medians of every patch of a search window using two distinct similarity measures: the Euclidean distance and the Kullback-Leibler divergence between Gaussian densities estimated from the patches. Computational experiments with 25 images corrupted by joint Gaussian and impulsive noises show that the proposed method is capable of producing, on average, significant higher PSNR and SSIM than the combination of the median filter and the Non-Local Means filter applied independently.
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPEW34M/45ALTQ2
zipped data URLhttp://urlib.net/zip/8JMKD3MGPEW34M/45ALTQ2
Languageen
Target Fileexample.pdf
User Groupalexandre.levada@ufscar.br
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/45PQ3RS
8JMKD3MGPEW34M/4742MCS
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination edition electronicmailaddress group isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url volume


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