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Reference TypeConference Proceedings
Identifier8JMKD3MGPAW/3RMQBE2
Repositorysid.inpe.br/sibgrapi/2018/08.25.17.24
Metadatasid.inpe.br/sibgrapi/2018/08.25.17.24.13
Sitesibgrapi.sid.inpe.br
Citation KeyAriasFeli:2018:ViDeQu
Author1 Arias, Rafael L. B.
2 Felinto, Alan Salvany
Affiliation1 Londrina State University (UEL)
2 Londrina State University (UEL)
TitleVideo Denoising Quality Assessment for Different Noise Distributions
Conference NameConference on Graphics, Patterns and Images, 31 (SIBGRAPI)
Year2018
EditorRoss, Arun
Gastal, Eduardo S. L.
Jorge, Joaquim A.
Queiroz, Ricardo L. de
Minetto, Rodrigo
Sarkar, Sudeep
Papa, João Paulo
Oliveira, Manuel M.
Arbeláez, Pablo
Mery, Domingo
Oliveira, Maria Cristina Ferreira de
Spina, Thiago Vallin
Mendes, Caroline Mazetto
Costa, Henrique Sérgio Gutierrez
Mejail, Marta Estela
Geus, Klaus de
Scheer, Sergio
Book TitleProceedings
DateOct. 29 - Nov. 1, 2018
Publisher CityLos Alamitos
PublisherIEEE Computer Society
Conference LocationFoz do Iguaçu, PR, Brazil
Keywordsdenoising, noise, video, quality metrics.
AbstractDenoising algorithms often presume a single noise model, for instance, Gaussian noise, but it has been observed that during acquisition, image and video sequences can be corrupted by different types of noise, which follow a distinct probability distribution model depending on the application. This paper aims to compare the performance of several denoising algorithms, among them Non-Local Means and Block-Matching 3D, and other classical techniques such as median, Gaussian, bilateral and anisotropic diffusion, by simulating different noise distributions in videos and comparing the methods efficiency in multiple scenarios. Objective evaluation uses structural similarity (SSIM) and provides video specific assessment scores with NTIA Video Quality Metric (VQM). Results show considerable differences between intraframe and interframe filtering quality, while variations in filtering responses to each type of noise contribute to more appropriate selection of techniques to noise reduction and provide insight to noise difficulty levels.
Languageen
Tertiary TypeFull Paper
FormatOn-line
Size19096 KiB
Number of Files1
Target FilePaper ID 55.pdf
Last Update2018:08.25.17.24.13 sid.inpe.br/banon/2001/03.30.15.38 administrator
Metadata Last Update2020:02.19.03.10.44 sid.inpe.br/banon/2001/03.30.15.38 administrator {D 2018}
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e-Mail Addressrafarias94@hotmail.com
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Content TypeExternal Contribution
Document Stagenot transferred
Next Higher Units8JMKD3MGPAW/3RPADUS
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History2018-08-25 17:24:13 :: rafarias94@hotmail.com -> administrator ::
2020-02-19 03:10:44 :: administrator -> :: 2018
Empty Fieldsaccessionnumber archivingpolicy archivist area callnumber copyholder copyright creatorhistory descriptionlevel dissemination doi edition electronicmailaddress group holdercode 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 versiontype volume
Access Date2020, Nov. 29

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