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Hyperspectral compressive sensing: a comparison of embedded GPU and ARM implementations

2019-09Conference object Restricted access
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dc.contributor.authorNascimento, Jose
dc.contributor.authorVéstias, Mário
dc.date.accessioned2020-03-10T08:29:31Z
dc.date.available2020-03-10T08:29:31Z
dc.date.issued2019-09
dc.description.abstractHyperspectral imaging involves the sensing of a large amount of spatial information across several adjacent wavelengths. Typically, hyperspectral images can be represented by a three-dimensional data cube. The collected data cube is extremely large to be transmitted from the satellite/airborne platform to the ground station. Compressive sensing (CS) is an emerging technique that acquire directly the compressed signal instead of acquiring the full data set. This reduces the amount of data that needs to be measured, transmitted and stored in first place. In this paper, a comparison of a CS method implementation for an ARM and for a GPU is conducted. This study takes into account the accuracy, the performance, and the power consumption for both implementations. The 256-cores GPU of a Jetson TX2 board, the dual-core ARM Cortex-A9 of a ZYNQ-7000 SoC FPGA and the quad-core ARM Cortex-A53 of a ZYNQ UltraScale SoC FPGA are the target platforms used for experimental validation. The obtained results indicate that the embedded GPU is faster but uses more power. Therefore, the most appropriate platform depends on the performance and power constraints of the project.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationNASCIMENTO, José M. P.; VÉSTIAS, Mário – Hyperspectral compressive sensing: a comparison of embedded GPU and ARM implementations. In Proceedings of SPIE, , Emerging Imaging and Sensing Technologies for Security and Defence IV. Strasbourg, France: SPIE, 2019. Vol. 11163, pp. 88-97pt_PT
dc.identifier.doihttps://doi.org/10.1117/12.2532581pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.21/11214
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherSociety of Photo-optical Instrumentation Engineerspt_PT
dc.relationUID/EEA/50008/2019 - FCTpt_PT
dc.subjectHypersectral compressive sensingpt_PT
dc.subjectParallel processingpt_PT
dc.subjectEmbedded systemspt_PT
dc.titleHyperspectral compressive sensing: a comparison of embedded GPU and ARM implementationspt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceStrasbourg, Francept_PT
oaire.citation.endPage97pt_PT
oaire.citation.startPage88pt_PT
oaire.citation.titleEmerging Imaging and Sensing Technologies for Security and Defence IVpt_PT
oaire.citation.volume11163pt_PT
person.familyNameNascimento
person.familyNameVéstias
person.givenNameJose
person.givenNameMário
person.identifier.ciencia-id6912-6F61-1964
person.identifier.ciencia-id4717-C2C7-3F2C
person.identifier.orcid0000-0002-5291-6147
person.identifier.orcid0000-0001-8556-4507
person.identifier.ridE-6212-2015
person.identifier.ridH-9953-2012
person.identifier.scopus-author-id55920018000
person.identifier.scopus-author-id14525867300
rcaap.rightsclosedAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublicationc7ffc6c0-1bdc-4f47-962a-a90dfb03073c
relation.isAuthorOfPublicationa7d22b29-c961-45ac-bc09-cd5e1002f1e8
relation.isAuthorOfPublication.latestForDiscoverya7d22b29-c961-45ac-bc09-cd5e1002f1e8

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