Asymptotic Behaviour of Total Generalised Variation

Konstantinos Papafitsoros, Tuomo Valkonen

Research output: Chapter in Book/Report/Conference proceedingChapter

7 Scopus citations


© 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
Original languageEnglish (US)
Title of host publicationScale Space and Variational Methods in Computer Vision
PublisherSpringer Nature
Number of pages13
ISBN (Print)9783319184609
StatePublished - Apr 28 2015
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): KUK-I1-007-43
Acknowledgements: 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”.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.


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