Analysis of Tensor Approximation for Compression-Domain Volume Visualization

As modern high-resolution imaging devices allow to acquire increasingly large and complex volume data sets, their effective and compact representation for visualization becomes a challenging task. The Tucker decomposition has already confirmed higher-order tensor approximation (TA) as a viable techn...

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Detalles Bibliográficos
Autores: Suter, Susanne, Pajarola, Renato, Ballester Ripoll, Rafael
Tipo de recurso: artículo
Fecha de publicación:2015
País:España
Institución:IE
Repositorio:Repositorio IE
OAI Identifier:oai:repositorio.ie.edu:20.500.14417/4017
Acceso en línea:https://doi.org/10.1016/j.cag.2014.10.002
https://hdl.handle.net/20.500.14417/4017
https://www.sciencedirect.com/science/article/abs/pii/S0097849314001289
Access Level:acceso abierto
Palabra clave:33 Ciencias Tecnológicas
ODS 9 - Industria, innovación e infraestructura
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spelling Analysis of Tensor Approximation for Compression-Domain Volume VisualizationSuter, SusannePajarola, RenatoBallester Ripoll, Rafael33 Ciencias TecnológicasODS 9 - Industria, innovación e infraestructuraAs modern high-resolution imaging devices allow to acquire increasingly large and complex volume data sets, their effective and compact representation for visualization becomes a challenging task. The Tucker decomposition has already confirmed higher-order tensor approximation (TA) as a viable technique for compressed volume representation; however, alternative decomposition approaches exist. In this work, we review the main TA models proposed in the literature on multiway data analysis and study their application in a visualization context, where reconstruction performance is emphasized along with reduced data representation costs. Progressive and selective detail reconstruction is a main goal for such representations and can efficiently be achieved by truncating an existing decomposition. To this end, we explore alternative incremental variations of the CANDECOMP/PARAFAC and Tucker models. We give theoretical time and space complexity estimates for every discussed approach and variant. Additionally, their empirical decomposition and reconstruction times and approximation quality are tested in both C++ and MATLAB implementations. Several scanned real-life exemplar volumes are used varying data sizes, initialization methods, degree of compression and truncation. As a result of this, we demonstrate the superiority of the Tucker model for most visualization purposes, while canonical-based models offer benefits only in limited situations.This work was supported in part by the Forschungskredit of the University of Zürich, the Swiss National Science Foundation (SNSF) (Projects nos. 200021_132521; ), as well as by the EU FP7 People Programme (Marie Curie Actions) under REA Grant Agreement no. 290227.YesPublishedElsevierUniversity of ZürichSwiss National Science Foundation (SNSF)People Programme (Marie Curie Actions)https://ror.org/02jjdwm7520252015info:eu-repo/semantics/articleapplication/pdfapplication/pdfhttps://doi.org/10.1016/j.cag.2014.10.002https://hdl.handle.net/20.500.14417/4017https://www.sciencedirect.com/science/article/abs/pii/S0097849314001289reponame:Repositorio IEinstname:IEInglésIE School of Science & Technology200021_132521290227IE UniversityApplied MathematicsAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:repositorio.ie.edu:20.500.14417/40172026-06-15T12:40:57Z
dc.title.none.fl_str_mv Analysis of Tensor Approximation for Compression-Domain Volume Visualization
title Analysis of Tensor Approximation for Compression-Domain Volume Visualization
spellingShingle Analysis of Tensor Approximation for Compression-Domain Volume Visualization
Suter, Susanne
33 Ciencias Tecnológicas
ODS 9 - Industria, innovación e infraestructura
title_short Analysis of Tensor Approximation for Compression-Domain Volume Visualization
title_full Analysis of Tensor Approximation for Compression-Domain Volume Visualization
title_fullStr Analysis of Tensor Approximation for Compression-Domain Volume Visualization
title_full_unstemmed Analysis of Tensor Approximation for Compression-Domain Volume Visualization
title_sort Analysis of Tensor Approximation for Compression-Domain Volume Visualization
dc.creator.none.fl_str_mv Suter, Susanne
Pajarola, Renato
Ballester Ripoll, Rafael
author Suter, Susanne
author_facet Suter, Susanne
Pajarola, Renato
Ballester Ripoll, Rafael
author_role author
author2 Pajarola, Renato
Ballester Ripoll, Rafael
author2_role author
author
dc.contributor.none.fl_str_mv University of Zürich
Swiss National Science Foundation (SNSF)
People Programme (Marie Curie Actions)
https://ror.org/02jjdwm75
dc.subject.none.fl_str_mv 33 Ciencias Tecnológicas
ODS 9 - Industria, innovación e infraestructura
topic 33 Ciencias Tecnológicas
ODS 9 - Industria, innovación e infraestructura
description As modern high-resolution imaging devices allow to acquire increasingly large and complex volume data sets, their effective and compact representation for visualization becomes a challenging task. The Tucker decomposition has already confirmed higher-order tensor approximation (TA) as a viable technique for compressed volume representation; however, alternative decomposition approaches exist. In this work, we review the main TA models proposed in the literature on multiway data analysis and study their application in a visualization context, where reconstruction performance is emphasized along with reduced data representation costs. Progressive and selective detail reconstruction is a main goal for such representations and can efficiently be achieved by truncating an existing decomposition. To this end, we explore alternative incremental variations of the CANDECOMP/PARAFAC and Tucker models. We give theoretical time and space complexity estimates for every discussed approach and variant. Additionally, their empirical decomposition and reconstruction times and approximation quality are tested in both C++ and MATLAB implementations. Several scanned real-life exemplar volumes are used varying data sizes, initialization methods, degree of compression and truncation. As a result of this, we demonstrate the superiority of the Tucker model for most visualization purposes, while canonical-based models offer benefits only in limited situations.
publishDate 2015
dc.date.none.fl_str_mv 2015
2025
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://doi.org/10.1016/j.cag.2014.10.002
https://hdl.handle.net/20.500.14417/4017
https://www.sciencedirect.com/science/article/abs/pii/S0097849314001289
url https://doi.org/10.1016/j.cag.2014.10.002
https://hdl.handle.net/20.500.14417/4017
https://www.sciencedirect.com/science/article/abs/pii/S0097849314001289
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv IE School of Science & Technology
200021_132521
290227
IE University
Applied Mathematics
dc.rights.none.fl_str_mv Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Repositorio IE
instname:IE
instname_str IE
reponame_str Repositorio IE
collection Repositorio IE
repository.name.fl_str_mv
repository.mail.fl_str_mv
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