| Literature DB >> 31396002 |
René Ciak1, Melanie Melching1, Otmar Scherzer1,2.
Abstract
We present an approach for variational regularization of inverse and imaging problems for recovering functions with values in a set of vectors. We introduce regularization functionals, which are derivative-free double integrals of such functions. These regularization functionals are motivated from double integrals, which approximate Sobolev semi-norms of intensity functions. These were introduced in Bourgain et al. (Another look at Sobolev spaces. In: Menaldi, Rofman, Sulem (eds) Optimal control and partial differential equations-innovations and applications: in honor of professor Alain Bensoussan's 60th anniversary, IOS Press, Amsterdam, pp 439-455, 2001). For the proposed regularization functionals, we prove existence of minimizers as well as a stability and convergence result for functions with values in a set of vectors.Entities:
Keywords: Bounded variation; Double integral; Fractional Sobolev space; Manifold-valued data; Metric; Non-convex; Regularization
Year: 2019 PMID: 31396002 PMCID: PMC6647495 DOI: 10.1007/s10851-018-00869-6
Source DB: PubMed Journal: J Math Imaging Vis ISSN: 0924-9907 Impact factor: 1.627