A NUMERICAL STUDY OF A MEAN CURVATURE DENOISING MODEL USING A NOVEL AUGMENTED LAGRANGIAN METHOD

作者：Zhu Wei^*

来源：Inverse Problems and Imaging, 2017, 11(6): 975-996.

DOI：10.3934/ipi.2017045

• Image denoising
• mean curvature
• augmented Lagrangian method
• high-order
• variational model

In this paper, we propose a new augmented Lagrangian method for the mean curvature based image denoising model [33]. Different from the previous works in [21, 35], this new method only involves two Lagrange multipliers, which significantly reduces the effort of choosing appropriate penalization parameters to ensure the convergence of the iterative process of finding the associated saddle points. With this new algorithm, we demonstrate the features of the model numerically, including the preservation of image contrasts and object corners, as well as its capability of generating smooth patches of image graphs. The data selection property and the role of the spatial mesh size for the model performance are also discussed.

• 出版日期2017-12