非凸总广义变差图像恢复模型

摘要

In order to preserve the geometric structure of image effectively, a novel nonconvex second-order total generalized variation image restoration model is proposed. The proposed model introduces a nonconvex sparse regularization term, and it is similar to the L0 norm, so the new model can protect the structure features better. In addition, for computing the new model effectively, the reweighted method and primal-dual method are presented. Experimental results show that the proposed model can get better results compared with the recent method.%　　为有效地保护图像的几何结构，提出了一种非凸二阶总广义变差图像恢复模型。该模型引入了类似于L0范数的非凸稀疏正则约束，模型能更好地保护图像的结构特征。为有效地计算该模型，采用迭代重加权和原始-对偶算法。数值实验表明，相比于最近的二阶总广义变差方法，该方法获得了较好的实验结果。