Efficient Algorithm for Isotropic and Anisotropic Total Variation Deblurring and Denoising | Zendy

Yuying Shi | Zendy; Qianshun Chang | Zendy

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Efficient Algorithm for Isotropic and Anisotropic Total Variation Deblurring and Denoising

Author(s) -

Yuying Shi,

Qianshun Chang

Publication year - 2013

Publication title -

journal of applied mathematics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.307

H-Index - 43

eISSN - 1687-0042

pISSN - 1110-757X

DOI - 10.1155/2013/797239

Subject(s) - deblurring , algorithm , solver , multigrid method , nonlinear system , mathematics , convergence (economics) , reduction (mathematics) , image restoration , mathematical optimization , image (mathematics) , computer science , image processing , mathematical analysis , geometry , computer vision , partial differential equation , physics , quantum mechanics , economic growth , economics

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

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