Abstract
In this paper, a new variational model for restoring blurred images with multiplicative noise is proposed. Based on the statistical property of the noise, a quadratic penalty function technique is utilized in order to obtain a strictly convex model under a mild condition, which guarantees the uniqueness of the solution and the stabilization of the algorithm. For solving the new convex variational model, a primal-dual algorithm is proposed, and its convergence is studied. The paper ends with a report on numerical tests for the simultaneous deblurring and denoising of images subject to multiplicative noise. A comparison with other methods is provided as well.
Original language | English |
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Pages (from-to) | 1598-1625 |
Number of pages | 28 |
Journal | SIAM Journal on Imaging Sciences |
Volume | 6 |
Issue number | 3 |
DOIs | |
Publication status | Published - 22 Aug 2013 |
Scopus Subject Areas
- Mathematics(all)
- Applied Mathematics
User-Defined Keywords
- Convexity
- Deblurring
- Multiplicative noise
- Primal-dual algorithm
- Total variation regularization
- Variational model