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http://dx.doi.org/10.18419/opus-12940
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DC Element | Wert | Sprache |
---|---|---|
dc.contributor.author | Sun, Kaicong | - |
dc.contributor.author | Tran, Trung-Hieu | - |
dc.contributor.author | Guhathakurta, Jajnabalkya | - |
dc.contributor.author | Simon, Sven | - |
dc.date.accessioned | 2023-04-13T09:13:37Z | - |
dc.date.available | 2023-04-13T09:13:37Z | - |
dc.date.issued | 2021 | de |
dc.identifier.issn | 1861-8200 | - |
dc.identifier.issn | 1861-8219 | - |
dc.identifier.other | 1843518384 | - |
dc.identifier.uri | http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-ds-129599 | de |
dc.identifier.uri | http://elib.uni-stuttgart.de/handle/11682/12959 | - |
dc.identifier.uri | http://dx.doi.org/10.18419/opus-12940 | - |
dc.description.abstract | Multi-image super-resolution (MISR) usually outperforms single-image super-resolution (SISR) under a proper inter-image alignment by explicitly exploiting the inter-image correlation. However, the large computational demand encumbers the deployment of MISR in practice. In this work, we propose a distributed optimization framework based on data parallelism for fast large-scale MISR using multi-GPU acceleration named FL-MISR. The scaled conjugate gradient (SCG) algorithm is applied to the distributed subfunctions and the local SCG variables are communicated to synchronize the convergence rate over multi-GPU systems towards a consistent convergence. Furthermore, an inner-outer border exchange scheme is performed to obviate the border effect between neighboring GPUs. The proposed FL-MISR is applied to the computed tomography (CT) system by super-resolving the projections acquired by subpixel detector shift. The SR reconstruction is performed on the fly during the CT acquisition such that no additional computation time is introduced. FL-MISR is extensively evaluated from different aspects and experimental results demonstrate that FL-MISR effectively improves the spatial resolution of CT systems in modulation transfer function (MTF) and visual perception. Comparing to a multi-core CPU implementation, FL-MISR achieves a more than 50× speedup on an off-the-shelf 4-GPU system. | en |
dc.description.sponsorship | Deutsche Forschungsgemeinschaft | de |
dc.description.sponsorship | Projekt DEAL | de |
dc.language.iso | en | de |
dc.relation.uri | doi:10.1007/s11554-021-01181-0 | de |
dc.rights | info:eu-repo/semantics/openAccess | de |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | de |
dc.subject.ddc | 004 | de |
dc.title | FL-MISR : fast large-scale multi-image super-resolution for computed tomography based on multi-GPU acceleration | en |
dc.type | article | de |
dc.date.updated | 2023-03-25T09:41:10Z | - |
ubs.fakultaet | Informatik, Elektrotechnik und Informationstechnik | de |
ubs.institut | Institut für Parallele und Verteilte Systeme | de |
ubs.publikation.seiten | 331-344 | de |
ubs.publikation.source | Journal of real-time image processing 19 (2022), S. 331-344 | de |
ubs.publikation.typ | Zeitschriftenartikel | de |
Enthalten in den Sammlungen: | 05 Fakultät Informatik, Elektrotechnik und Informationstechnik |
Dateien zu dieser Ressource:
Datei | Beschreibung | Größe | Format | |
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s11554-021-01181-0.pdf | 2,67 MB | Adobe PDF | Öffnen/Anzeigen |
Diese Ressource wurde unter folgender Copyright-Bestimmung veröffentlicht: Lizenz von Creative Commons