Journal of Applied Mathematics

  • J. Appl. Math.
  • Volume 2013, Special Issue (2012), Article ID 797239, 14 pages.

Efficient Algorithm for Isotropic and Anisotropic Total Variation Deblurring and Denoising

Yuying Shi and Qianshun Chang

Full-text: Open access

Abstract

A new deblurring and denoising algorithm is proposed, for isotropic total variation-based image restoration. The algorithm consists of an efficient solver for the nonlinear system and an acceleration strategy for the outer iteration. For the nonlinear system, the split Bregman method is used to convert it into linear system, and an algebraic multigrid method is applied to solve the linearized system. For the outer iteration, we have conducted formal convergence analysis to determine an auxiliary linear term that significantly stabilizes and accelerates the outer iteration. Numerical experiments demonstrate that our algorithm for deblurring and denoising problems is efficient.

Article information

Source
J. Appl. Math., Volume 2013, Special Issue (2012), Article ID 797239, 14 pages.

Dates
First available in Project Euclid: 14 March 2014

Permanent link to this document
https://projecteuclid.org/euclid.jam/1394806082

Digital Object Identifier
doi:10.1155/2013/797239

Mathematical Reviews number (MathSciNet)
MR3035164

Zentralblatt MATH identifier
1266.65039

Citation

Shi, Yuying; Chang, Qianshun. Efficient Algorithm for Isotropic and Anisotropic Total Variation Deblurring and Denoising. J. Appl. Math. 2013, Special Issue (2012), Article ID 797239, 14 pages. doi:10.1155/2013/797239. https://projecteuclid.org/euclid.jam/1394806082


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