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Convergence in variation for the multidimensional generalized sampling series and applications to smoothing for digital image processing
2020
Annales Academiae Scientiarum Fennicae: Mathematica
In this paper we study the problem of the convergence in variation for the generalized sampling series based upon averaged-type kernels in the multidimensional setting. As a crucial tool, we introduce a family of operators of sampling-Kantorovich type for which we prove convergence in L p on a subspace of L p (R N ): therefore we obtain the convergence in variation for the multidimensional generalized sampling series by means of a relation between the partial derivatives of such operators
doi:10.5186/aasfm.2020.4532
fatcat:qbkaasmt6bee7ilvut236bok4q