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A Unified Framework for the Restoration of Images Corrupted by Additive White Noise

  • Alessandro Lanza
  • Federica Sciacchitano
  • Serena MorigiEmail author
  • Fiorella Sgallari
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10302)

Abstract

We propose a robust variational model for the restoration of images corrupted by blur and the general class of additive white noises. The solution of the non-trivial optimization problem, due to the non-smooth non-convex proposed model, is efficiently obtained by an Alternating Directions Method of Multipliers (ADMM), which in particular reduces the solution to a sequence of convex optimization sub-problems. Numerical results show the potentiality of the proposed model for restoring blurred images corrupted by several kinds of additive white noises.

Keywords

Variational image restoration Additive white noise Total Variation Non-convex non-smooth optimization ADMM 

Notes

Acknowledgements

This work was supported by the “National Group for Scientific Computation (GNCS-INDAM)” and by ex60% project by the University of Bologna “Funds for selected research topics”.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Alessandro Lanza
    • 1
  • Federica Sciacchitano
    • 2
  • Serena Morigi
    • 1
    Email author
  • Fiorella Sgallari
    • 1
  1. 1.Department of MathematicsUniversity of BolognaBolognaItaly
  2. 2.Department of MathematicsUniversity of GenovaGenovaItaly

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