Image Inpainting Based on Structural Tensor Edge Intensity Model  

作　　者：Jing Wang Yan-Hong Zhou Hai-Feng Sima Zhan-Qiang Huo Ai-Zhong Mi 

机构地区：[1]College of Computer Science and Technology,Henan Polytechnic University,Jiaozuo 454003,China

出　　处：《International Journal of Automation and computing》2021年第2期256-265,共10页国际自动化与计算杂志（英文版）

基　　金：This work was supported by National Science Foundation of China(Nos.61401150,61602157 and 61872311);Key Science and Technology Program of Henan Province(Nos.182102210053 and 202102210167);Excellent Young Teachers Program of Henan Polytechnic University(No.2019XQG-02).

摘　　要：In the exemplar-based image inpainting approach,there are usually two major problems:the unreasonable calculation of priority and only considering the color features in the patch lookup strategy.In this paper,we propose an image inpainting approach based on the structural tensor edge intensity model.First,we use the progressive scanning inpainting method to avoid the image filling order being affected by the priority function.Then,we use the edge intensity model to build the patches similarity function for correctly identifying the local image structure.Finally,the balance operator is used to restrict the excessive propagation of structural information to ensure the correct structural reconstruction.The experimental results show that the our approach is comparable and even superior to some state-of-the-art inpainting algorithms.

关 键 词：Exemplar-based technique image inpainting structural tensor edge intensity model structure propagation balance operator 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]