A two-step model for image denoising using a duality strategy and surface fitting

Authors:
Zhi-Feng Pang;Yu-Fei Yang
Affiliations:
College of Mathematics and Information Science, Henan University, Kaifeng, 475004, China;College of Mathematics and Econometrics, Hunan University, Changsha, 410082, China
Venue:
Journal of Computational and Applied Mathematics
Year:
2010

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Abstract

In order to alleviate the staircase effect or the edge blurring in the course of the image denoising, we propose a two-step model based on the duality strategy. In fact, this strategy follows the observation that the dual variable of the restored image can be looked at as the normal vector. So we first obtain the dual variable and then reconstruct the image by fitting the dual variable. Following the augmented Lagrangian strategy, we propose a projection gradient method for solving this two-step model. We also give some convergence analyses of the proposed projection gradient method. Several numerical experiments are tested to compare our proposed model with the ROF model and the LLT model.