Handle URI:
http://hdl.handle.net/10754/597621
Title:
Asymptotic Behaviour of Total Generalised Variation
Authors:
Papafitsoros, Konstantinos; Valkonen, Tuomo
Abstract:
© Springer International Publishing Switzerland 2015. The recently introduced second order total generalised variation functional TGV2 β,α has been a successful regulariser for image processing purposes. Its definition involves two positive parameters α and β whose values determine the amount and the quality of the regularisation. In this paper we report on the behaviour of TGV2 β,α in the cases where the parameters α, β as well as their ratio β/α becomes very large or very small. Among others, we prove that for sufficiently symmetric two dimensional data and large ratio β/α, TGV2 β,α regularisation coincides with total variation (TV) regularization
Citation:
Papafitsoros K, Valkonen T (2015) Asymptotic Behaviour of Total Generalised Variation. Scale Space and Variational Methods in Computer Vision: 702–714. Available: http://dx.doi.org/10.1007/978-3-319-18461-6_56.
Publisher:
Springer Science + Business Media
Journal:
Scale Space and Variational Methods in Computer Vision
KAUST Grant Number:
KUK-I1-007-43
Issue Date:
2015
DOI:
10.1007/978-3-319-18461-6_56
Type:
Book Chapter
ISSN:
0302-9743; 1611-3349
Sponsors:
This work is supported by the King Abdullah University for Science and Technology (KAUST) Award No. KUK-I1-007-43. The first author acknowledges further support by the Cambridge Centre for Analysis (CCA) and the Engineering and Physical Sciences Research Council (EPSRC). The second author acknowledges further support from EPSRC grant EP/M00483X/1 “Efficient computational tools for inverse imaging problems”.
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Publications Acknowledging KAUST Support

Full metadata record

DC FieldValue Language
dc.contributor.authorPapafitsoros, Konstantinosen
dc.contributor.authorValkonen, Tuomoen
dc.date.accessioned2016-02-25T12:43:12Zen
dc.date.available2016-02-25T12:43:12Zen
dc.date.issued2015en
dc.identifier.citationPapafitsoros K, Valkonen T (2015) Asymptotic Behaviour of Total Generalised Variation. Scale Space and Variational Methods in Computer Vision: 702–714. Available: http://dx.doi.org/10.1007/978-3-319-18461-6_56.en
dc.identifier.issn0302-9743en
dc.identifier.issn1611-3349en
dc.identifier.doi10.1007/978-3-319-18461-6_56en
dc.identifier.urihttp://hdl.handle.net/10754/597621en
dc.description.abstract© Springer International Publishing Switzerland 2015. The recently introduced second order total generalised variation functional TGV2 β,α has been a successful regulariser for image processing purposes. Its definition involves two positive parameters α and β whose values determine the amount and the quality of the regularisation. In this paper we report on the behaviour of TGV2 β,α in the cases where the parameters α, β as well as their ratio β/α becomes very large or very small. Among others, we prove that for sufficiently symmetric two dimensional data and large ratio β/α, TGV2 β,α regularisation coincides with total variation (TV) regularizationen
dc.description.sponsorshipThis work is supported by the King Abdullah University for Science and Technology (KAUST) Award No. KUK-I1-007-43. The first author acknowledges further support by the Cambridge Centre for Analysis (CCA) and the Engineering and Physical Sciences Research Council (EPSRC). The second author acknowledges further support from EPSRC grant EP/M00483X/1 “Efficient computational tools for inverse imaging problems”.en
dc.publisherSpringer Science + Business Mediaen
dc.subjectAsymptotic behaviour of regularisersen
dc.subjectRegularisation parametersen
dc.subjectTotal generalised variationen
dc.subjectTotal variationen
dc.titleAsymptotic Behaviour of Total Generalised Variationen
dc.typeBook Chapteren
dc.identifier.journalScale Space and Variational Methods in Computer Visionen
dc.contributor.institutionUniversity of Cambridge, Cambridge, United Kingdomen
kaust.grant.numberKUK-I1-007-43en
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