images corrupted by Poisson noise frequently appear in various applications
such as medical and astronomical imaging. Due to the strong edge preserving
ability, the Total variation (TV) regularization has been developed as an
important regularization method to solve the Poisson denoising problem.
However, TV introduces staircase effects. In this paper, we propose a hybrid
variational model which takes advantages of the wavelet tight frame and TV. An
efficient iterative algorithm based on the augmented Lagrangian technique is
proposed. Under some conditions, the convergence property of the proposed
algorithm is also investigated. Numerical experiments illustrate the
effectiveness of the proposed method.