Image restoration is a common problem in visual process. In this paper, a modified minimization model is presented, which combines the L1 and L2 fidelity terms with a combined quadratic L2 and TV regularizer just as the regularizer of Cai et al. (2013). The combined regularizer has the priorities of preserving desirable edges and ensuring several kinds of noises can be removed clearly. Split-Bregman algorithm is effi- ciently employed to solve this model and convergence analysis is also discussed. Moreover, we extend the proposed model and algorithm for image restoration involving blurry images and color images. Experimental results show that our proposed model and algorithm have good performance both in visual and ISNR values for different kinds of blurs and noises including mixed noise.

Convergence of a second-order shock-capturing scheme for the system of isentropic gas dynamics with $ {L^\infty }$ initial data is established by analyzing the entropy dissipation measures. This scheme is modified from the classical MUSCL scheme to treat the vacuum problem in gas fluids and to capture local entropy near shock waves. Convergence of this scheme for the piston problem is also discussed.

This is the first of a series of papers on the subject of projection methods for viscous incompressible flow calculations. The purpose of these papers is to provide a thorough understanding of the numerical phenomena involved in the projection methods, particularly when boundaries are present, and point to ways of designing more efficient, robust, and accurate numerical methods based on the primitive variable formulation. This paper contains the following topics: 1. convergence and optimal error estimates for both velocity and pressure up to the boundary; 2. explicit characterization of the numerical boundary layers in the pressure approximations and the intermediate velocity fields; 3. the effect of choosing different numerical boundary conditions at the projection step. We will show that a different choice of boundary conditions gives rise to different boundary layer structures. In particular, the straightforward Dirichlet boundary condition for the pressure leads to O(1) numerical boundary layers in the pressure and deteriorates the accuracy in the interior; and 4. postprocessing the numerical solutions to get more accurate approximations for the pressure.

We begin a systematical study on the effect of numerical viscosities. In this paper we investigate the behavior of shock-capturing methods for slowly moving shocks. It is known that for slowly moving shocks even a first-order scheme, such as the Godunov or Roe type methods, will generate downstream oscillatory wave patterns that cannot be effectively damped by the dissipation of these first-order schemes. The purpose of this paper is to understand the formation and behavior of these downstream patterns. Our study shows that the downstream errors are generated by the unsteady nature of the viscous shock profiles and behave diffusively. The scenario is as follows. When solving the compressible Euler equations by shock capturing methods, the smeared density profile introduces a momentum spike at the shock location if the shock moves slowly. Downstream waves will necessarily emerge in order to balance the momentum mass carried by the spike for the momentum conservation. Although each family of waves decays inl∞andl2while they preserve the same mass, the perturbing nature of the viscous or spike profile is a constant source for the generation of new downstream waves, causing spurious solutions foralltime. Higher order TVD or ENO type interpolations accentuate this problem.

In this paper, we review some recent progress made in [4, 5, 6] on finite difference schemes for viscous incompressible flows using vorticity formulation. The main purpose of this series of papers [4, 5, 6] is to resurrect the idea of using local vorticity boundary condition for unsteady calculation. The emphasis is on simplicity of the methods. Three main issues will be discussed: efficient time-stepping procedures and cell Reynolds number constraints, efficient methods in 3D on non-staggered grids and efficient high order methods using compact differencing.