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A TGV Regularized Wavelet Based Zooming Model

  • Kristian Bredies
  • Martin Holler
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7893)

Abstract

We propose and state a novel scheme for image magnification. It is formulated as a minimization problem which incorporates a data fidelity and a regularization term. Data fidelity is modeled using a wavelet transformation operator while the Total Generalized Variation functional of second order is applied for regularization. Well-posedness is obtained in a function space setting and an efficient numerical algorithm is developed. Numerical experiments confirm a high quality of the magnified images. In particular, with an appropriate choice of wavelets, geometrical information is preserved.

Keywords

Scaling Function Wavelet Function Haar Wavelet Riesz Basis Bound Lipschitz Domain 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Kristian Bredies
    • 1
  • Martin Holler
    • 1
  1. 1.Institute of Mathematics and Scientific ComputingUniversity of GrazGrazAustria

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