Publikation: Image Super-Resolution Framework with Multi-Channel Constraints
Lade...
Dateien
Zu diesem Dokument gibt es keine Dateien.
Datum
2007
Autor:innen
Herausgeber:innen
ISSN der Zeitschrift
Electronic ISSN
ISBN
Bibliografische Daten
Verlag
Schriftenreihe
Auflagebezeichnung
DOI (zitierfähiger Link)
Internationale Patentnummer
Angaben zur Forschungsförderung
Projekt
Open Access-Veröffentlichung
Core Facility der Universität Konstanz
Titel in einer weiteren Sprache
Publikationstyp
Beitrag zu einem Konferenzband
Publikationsstatus
Published
Erschienen in
IEEE, , ed.. IEEE International Conference on Multimedia and Expo, 2007 : ICME 2007 ; 2-5 July 2007, Beijing International Convention Center, Beijing, China ; proceedings. Piscataway, NJ: IEEE, 2007, pp. 456-459. ISBN 1-4244-1016-9. Available under: doi: 10.1109/ICME.2007.4284685
Zusammenfassung
Super-resolution reconstruction (SR) has been widely used to produce a high resolution (HR) image from several low resolution (LR) ones. In current methods, a LR image is selected as benchmark and upsampled as the initial SR estimate. This SR estimate is then degraded and compared with the adjacent LR frames for correction. Considering LR images captured from the same HR image with different translation at different instants, SR outputs by different benchmark selection should be identical, so tighter constraints can be designed to limit SR indetermination and to produce better SR images. In this paper, we propose a novel SR framework and prove its efficiency statistically using the unbiased estimation. Experimental results indicate that the proposed algorithm outperforms some existing approaches in both subjective and objective terms.
Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
004 Informatik
Schlagwörter
Konferenz
2007 IEEE International Conference on Multimedia and Expo, ICME, 2. Juli 2007 - 5. Juli 2007, Beijing
Rezension
undefined / . - undefined, undefined
Zitieren
ISO 690
WANG, Ci, Ping XUE, Weisi LIN, Minmin SHEN, 2007. Image Super-Resolution Framework with Multi-Channel Constraints. 2007 IEEE International Conference on Multimedia and Expo, ICME. Beijing, 2. Juli 2007 - 5. Juli 2007. In: IEEE, , ed.. IEEE International Conference on Multimedia and Expo, 2007 : ICME 2007 ; 2-5 July 2007, Beijing International Convention Center, Beijing, China ; proceedings. Piscataway, NJ: IEEE, 2007, pp. 456-459. ISBN 1-4244-1016-9. Available under: doi: 10.1109/ICME.2007.4284685BibTex
@inproceedings{Wang2007Image-30709,
year={2007},
doi={10.1109/ICME.2007.4284685},
title={Image Super-Resolution Framework with Multi-Channel Constraints},
isbn={1-4244-1016-9},
publisher={IEEE},
address={Piscataway, NJ},
booktitle={IEEE International Conference on Multimedia and Expo, 2007 : ICME 2007 ; 2-5 July 2007, Beijing International Convention Center, Beijing, China ; proceedings},
pages={456--459},
editor={IEEE},
author={Wang, Ci and Xue, Ping and Lin, Weisi and Shen, Minmin}
}RDF
<rdf:RDF
xmlns:dcterms="http://purl.org/dc/terms/"
xmlns:dc="http://purl.org/dc/elements/1.1/"
xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
xmlns:bibo="http://purl.org/ontology/bibo/"
xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#"
xmlns:foaf="http://xmlns.com/foaf/0.1/"
xmlns:void="http://rdfs.org/ns/void#"
xmlns:xsd="http://www.w3.org/2001/XMLSchema#" >
<rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/30709">
<void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
<dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
<foaf:homepage rdf:resource="http://localhost:8080/"/>
<dc:creator>Shen, Minmin</dc:creator>
<dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2015-04-09T09:52:59Z</dcterms:available>
<dcterms:abstract xml:lang="eng">Super-resolution reconstruction (SR) has been widely used to produce a high resolution (HR) image from several low resolution (LR) ones. In current methods, a LR image is selected as benchmark and upsampled as the initial SR estimate. This SR estimate is then degraded and compared with the adjacent LR frames for correction. Considering LR images captured from the same HR image with different translation at different instants, SR outputs by different benchmark selection should be identical, so tighter constraints can be designed to limit SR indetermination and to produce better SR images. In this paper, we propose a novel SR framework and prove its efficiency statistically using the unbiased estimation. Experimental results indicate that the proposed algorithm outperforms some existing approaches in both subjective and objective terms.</dcterms:abstract>
<dc:contributor>Xue, Ping</dc:contributor>
<dc:language>eng</dc:language>
<dc:creator>Lin, Weisi</dc:creator>
<dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
<dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2015-04-09T09:52:59Z</dc:date>
<dc:contributor>Shen, Minmin</dc:contributor>
<dc:creator>Xue, Ping</dc:creator>
<dc:contributor>Lin, Weisi</dc:contributor>
<dcterms:issued>2007</dcterms:issued>
<bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/30709"/>
<dc:contributor>Wang, Ci</dc:contributor>
<dcterms:title>Image Super-Resolution Framework with Multi-Channel Constraints</dcterms:title>
<dc:creator>Wang, Ci</dc:creator>
</rdf:Description>
</rdf:RDF>Interner Vermerk
xmlui.Submission.submit.DescribeStep.inputForms.label.kops_note_fromSubmitter
Prüfungsdatum der Dissertation
Finanzierungsart
Kommentar zur Publikation
Allianzlizenz
Corresponding Authors der Uni Konstanz vorhanden
Internationale Co-Autor:innen
Universitätsbibliographie
Nein
