A first-order image denoising model for staircase reduction. (English) Zbl 1434.94018
Summary: 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 [L. I. Rudin et al., Physica D 60, No. 1–4, 259–268 (1992; Zbl 0780.49028)]. 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.
MSC:
| 94A08 | Image processing (compression, reconstruction, etc.) in information and communication theory |
| 65K10 | Numerical optimization and variational techniques |
| 65M32 | Numerical methods for inverse problems for initial value and initial-boundary value problems involving PDEs |
Citations:
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