Total Variation Image Restoration Method Based on Subspace Optimization

Abstract

The alternating direction method is widely applied in total variation image restoration. However, the search directions of the method are not accurate enough. In this paper, one method based on the subspace optimization is proposed to improve its optimization performance. This method corrects the search directions of primal alternating direction method by using the energy function and a linear combination of the previous search directions. In addition, the convergence of the primal alternating direction method is proven under some weaker conditions. Thus the convergence of the corrected method could be easily obtained since it has same convergence with the primal alternating direction method. Numerical examples are given to show the performance of proposed method finally.