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.
Bibliographical note© 2013 SIAM.
- Multiplicative noise
- Primal-dual algorithm
- Total variation regularization
- Variational model
Dong, Y., & Tieyong Zeng (2013). A Convex Variational Model for Restoring Blurred Images with Multiplicative Noise. S I A M Journal on Imaging Sciences, 6(3), 1598-1625. https://doi.org/10.1137/120870621