KAUST Grant NumberKUK-I1-007-43
Permanent link to this recordhttp://hdl.handle.net/10754/597621
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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
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.
SponsorsThis 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”.