Journal of Scientific Computing

, Volume 54, Issue 2–3, pp 549–576 | Cite as

Bregmanized Domain Decomposition for Image Restoration

  • Andreas Langer
  • Stanley Osher
  • Carola-Bibiane Schönlieb
Article

Abstract

Computational problems of large-scale data are gaining attention recently due to better hardware and hence, higher dimensionality of images and data sets acquired in applications. In the last couple of years non-smooth minimization problems such as total variation minimization became increasingly important for the solution of these tasks. While being favorable due to the improved enhancement of images compared to smooth imaging approaches, non-smooth minimization problems typically scale badly with the dimension of the data. Hence, for large imaging problems solved by total variation minimization domain decomposition algorithms have been proposed, aiming to split one large problem into N>1 smaller problems which can be solved on parallel CPUs. The N subproblems constitute constrained minimization problems, where the constraint enforces the support of the minimizer to be the respective subdomain.

In this paper we discuss a fast computational algorithm to solve domain decomposition for total variation minimization. In particular, we accelerate the computation of the subproblems by nested Bregman iterations. We propose a Bregmanized Operator Splitting–Split Bregman (BOS-SB) algorithm, which enforces the restriction onto the respective subdomain by a Bregman iteration that is subsequently solved by a Split Bregman strategy. The computational performance of this new approach is discussed for its application to image inpainting and image deblurring. It turns out that the proposed new solution technique is up to three times faster than the iterative algorithm currently used in domain decomposition methods for total variation minimization.

Keywords

Domain decomposition Bregman distance Iterative Bregman algorithms Image restoration Total variation 

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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Andreas Langer
    • 1
  • Stanley Osher
    • 2
  • Carola-Bibiane Schönlieb
    • 3
  1. 1.Johann Radon Institute for Computational and Applied Mathematics (RICAM)Austrian Academy of SciencesLinzAustria
  2. 2.Department of MathematicsUCLALos AngelesUSA
  3. 3.Department of Applied Mathematics and Theoretical Physics (DAMTP)University of CambridgeCambridgeUK

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