A first-order image denoising model for staircase reduction



In this paper, we consider a total variation–based image denoising model that is able to alleviate the well-known staircasing phenomenon possessed by the Rudin-Osher-Fatemi model (Rudin et al., Phys. D 60, 259–268, 30). To minimize this variational model, we employ augmented Lagrangian method (ALM). Convergence analysis is established for the proposed algorithm. Numerical experiments are presented to demonstrate the features of the proposed model and also show the efficiency of the proposed numerical method.


Image denoising Augmented Lagrangian method Variational model 

Mathematics Subject Classification (2010)

94A08 65K10 65M32 


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The author would like to thank the anonymous referees for their valuable comments and suggestions, which have helped very much to improve the presentation of this paper.


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Authors and Affiliations

  1. 1.Department of MathematicsUniversity of AlabamaTuscaloosaUSA

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