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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPEW34M/43BC4T5
Repositorysid.inpe.br/sibgrapi/2020/09.29.19.17
Last Update2020:09.29.19.17.42 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2020/09.29.19.17.42
Metadata Last Update2022:06.14.00.00.12 (UTC) administrator
DOI10.1109/SIBGRAPI51738.2020.00020
Citation KeyFerreiraGastSchnNava:2020:PeErAn
TitlePerformance and error analysis of recursive edge-aware Gaussian filters on GPUs
FormatOn-line
Year2020
Access Date2024, Apr. 29
Number of Files1
Size2072 KiB
2. Context
Author1 Ferreira, Hermes H.
2 Gastal, Eduardo S. L.
3 Schnorr, Lucas M.
4 Navaux, Philippe O. A.
Affiliation1 Institute of Mathematics and Statistics - UFRGS
2 Institute of Informatics - UFRGS
3 Institute of Informatics - UFRGS
4 Institute of Informatics - UFRGS
EditorMusse, Soraia Raupp
Cesar Junior, Roberto Marcondes
Pelechano, Nuria
Wang, Zhangyang (Atlas)
e-Mail Addresshermes.hofmeister@ufrgs.br
Conference NameConference on Graphics, Patterns and Images, 33 (SIBGRAPI)
Conference LocationPorto de Galinhas (virtual)
Date7-10 Nov. 2020
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2020-09-29 19:17:42 :: hermes.hofmeister@ufrgs.br -> administrator ::
2022-06-14 00:00:12 :: administrator -> hermes.hofmeister@ufrgs.br :: 2020
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
Keywordsedge-aware filtering
GPU processing
high-performance computing
recursive filtering
image processing
AbstractWe present a schematic for image edge-aware Gaussian GPU filtering which has linear complexity on the number of pixels of the image. It allows us to reduce the execution time as we increase the number of Streaming Multiprocessors (SMs) on the GPU. We make use of a domain transformation and use a complex-valued recursive formulation of the Gaussian filter. The algorithm partitions the image in disjoint regions, where we compute in parallel the filtering operations, avoiding communication between regions. Our implementation leads to a real-time solution using a modern GPU. With the RTX 2080 Ti, we achieved an execution time of less than 10 milliseconds for 2 filtering iterations on high-resolution RGB images of dimensions 2048x2048.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2020 > Performance and error...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > Performance and error...
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPEW34M/43BC4T5
zipped data URLhttp://urlib.net/zip/8JMKD3MGPEW34M/43BC4T5
Languageen
Target FileFerreira_et_al_2020_Performance_edge-aware_filters_GPUs.pdf
User Grouphermes.hofmeister@ufrgs.br
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/43G4L9S
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2020/10.28.20.46 6
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
7. Description control
e-Mail (login)hermes.hofmeister@ufrgs.br
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