Affiliations: [a] Key Laboratory of Optimization and Control for Complex Systems, School of Information Science and Engineering, Hunan Institution of Science and Technology, Yueyang, 414006, Hunan, China | [b] Research Center for Heterogeneous Computing and Its Application, Hunan Institute of Science and Technology, Yueyang 414006, Hunan, China
Correspondence:
[*]
Corresponding authors: Guoyun Zhang, Research Center for Heterogeneous Computing and Its Application, Hunan Institute of Science and Technology, Yueyang 414006, Hunan, China. E-mail: gyzhang@hnist.edu.cn. Xin Peng, E-mail: Peng-xin@gmail.com.
Abstract: Image inpainting is an effective method to repair damaged image. In this paper, we mainly studied some typical image inpainting models and analyzed these corresponding repair qualities. Firstly, we studied three typical algorithms based on PDE (Partial Differential Equation) model to repair images whose damaged areas are relative small. And then we studied the image inpainting algorithm based on texture synthesis. This kind of inpainting algorithm is suitable for image with large damaged area. Finally, we studied Criminisi inpainting algorithm based on image segmentation in detail, on which we proposed an improved priority formula image repair algorithm, the simulation results indicate that the improved algorithm of this paper showed better performance in repair quality from both subjective and objective aspects.
