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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPBW34M/3JMNT4P
Repositorysid.inpe.br/sibgrapi/2015/06.19.20.59
Last Update2015:06.19.20.59.50 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2015/06.19.20.59.50
Metadata Last Update2022:06.14.00.08.09 (UTC) administrator
DOI10.1109/SIBGRAPI.2015.47
Citation KeySeibelJrGoldRoch:2015:FaEfGe
TitleFast and Effective Geometric K-Nearest Neighbors Multi-Frame Super-Resolution
FormatOn-line
Year2015
Access Date2024, Apr. 28
Number of Files1
Size564 KiB
2. Context
Author1 Seibel Junior, Hilario
2 Goldenstein, Siome
3 Rocha, Anderson
Affiliation1 Instituto Federal do Espirito Santo, Universidade Estadual de Campinas
2 Universidade Estadual de Campinas
3 Universidade Estadual de Campinas
EditorPapa, Joćo Paulo
Sander, Pedro Vieira
Marroquim, Ricardo Guerra
Farrell, Ryan
e-Mail Addresshsjunior@ifes.edu.br
Conference NameConference on Graphics, Patterns and Images, 28 (SIBGRAPI)
Conference LocationSalvador, BA, Brazil
Date26-29 Aug. 2015
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2015-06-19 20:59:50 :: hsjunior@ifes.edu.br -> administrator ::
2022-06-14 00:08:09 :: administrator -> :: 2015
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
Keywordssuper-resolution
geometric k-NN
multi-frame
burst
mobile devices
AbstractMulti-frame super-resolution is possible when there is motion and non-redundant information from a sequence of low-resolution input images. Remote sensors, surveillance videos and modern mobile phones are examples of devices able to easily gather multiple images of a same scene. However, combining a large number of frames into a higher resolution image may not be computationally feasible by complex super-resolution techniques. We discuss herein a set of simple and effective high-performance algorithms to fastly super-resolve several low-resolution images in an always-on low-power environment, with possible applications in mobile computing, forensics, and biometrics. The algorithms rely on geometric k-nearest neighbors to decide which information to consider in each high-resolution pixel, have a low memory footprint and run in linear time as we increase the number of low-resolution input images. Finally, we suggest a minimum number of input images for multi-frame super-resolution, considering that we expect a good response as fast as possible.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2015 > Fast and Effective...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > Fast and Effective...
doc Directory Contentaccess
source Directory Contentthere are no files
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPBW34M/3JMNT4P
zipped data URLhttp://urlib.net/zip/8JMKD3MGPBW34M/3JMNT4P
Languageen
Target FilePID3771795.pdf
User Grouphsjunior@ifes.edu.br
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPBW34M/3K24PF8
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2015/08.03.22.49 5
sid.inpe.br/sibgrapi/2022/06.10.21.49 2
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 schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url volume


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