Image Inpainting Based on Sparse Representation with Dictionary Pre-clustering

摘要：

　　This paper proposed a new image inpainting algorithm based on sparse representation.In traditional exemplar-based methods,the image patch is inpainted by the best matched patch from the source region.This greedy search will introduce unwanted objects and has huge time consuming.The proposed algorithm directly employs all the known image patches to form an over-complete dictionary.And then,the overcomplete dictionary is clustered into several sub-dictionaries.Finally,the unrepaired image patches are repaired over their corresponding closest sub-dictionaries through non-negative orthogonal matching pursuit algorithm.Experimental results show that the proposed method achieves superior performance than state-of-the-art methods.In addition,the time complexity is greatly reduced in comparison with the traditional exemplar-based inpainting algorithm.

关键词： Image inpainting Sparse representation Over-complete dictionary

作者: Kai Xu Nannan Wang Xinbo Gao

作者单位: State Key Laboratory of Integrated Services Networks,School of Electronic Engineering,Xidian Univers State Key Laboratory of Integrated Services Networks,School of Telecommunications Engineering,Xidian

会议类型: 国际会议

会议名称: 第七届全国模式识别学术会议(The 7th Chinese Conference on Pattern Recognition,CCPR2016)

会议地点: 成都

会议语种:英文

页码: 245-258

在线出版日期: 2016-11-03（万方平台首次上网日期，不代表论文的发表时间）