一种结合全局一致性与局部连续性的壁画修复方法  

A Global Uniform and Local Continuity Repair Method for Murals Inpainting

作　　者：王欢 李利 李庆 邓筠钰 商惠敏[1] WANG Huan;LI Li;LI Qing;Deng Junyu;SHANG Huiming(Industrial Technology Research Center,Guangdong Institute of Scientific&Technical Information,Guangzhou 510033,China;College of Civil and Transportation Engineering,Shenzhen University,Shenzhen 518061,China;School of Automation Science and Engineering,South China University of Technology,Guangzhou 510641,China)

机构地区：[1]广东省科学技术情报研究所产业技术研究中心,广东广州510033 [2]深圳大学土木与交通工程学院,广东深圳518061 [3]华南理工大学自动化科学与工程学院,广东广州510641

出　　处：《湖南大学学报（自然科学版）》2022年第6期135-145,共11页Journal of Hunan University:Natural Sciences

基　　金：广东省重点领域研发计划项目(2018B010112001);广东省科技计划项目(XMHT-202103008)。

摘　　要：提出了一种全局一致性和局部连续性结合的壁画修复算法.主要利用线性系统和图像修复间所蕴含的关系,构建具有全局过完备特性的相似块集合字典,同时构造弹性网正则化下的稀疏修复模型,并用同伦-最小角回归法求解出过完备字典下的稀疏系数;通过字典与系数的线性组合,得到待修复区域的全局特征;之后提出一种基于领域相似特性的局部特征估计方法,得到待修复区域的局部特征;最后对上述得到的全局和局部特征信息做线性加权,完成整个待修复区域的填充.实验结果表明,本算法能很好地解决相关修复算法在修复时所出现的纹理错误填充、结构不连续以及“块效应”等现象,并且得到较好的修复结果 .This paper proposes a global uniform and local continuity repair method for mural image inpainting.It uses the relationship between linear system and image repair to construct the similarity-preserving overcomplete dictionary with global weighted feature. Meanwhile, a novel sparse repair model with elastic net regularization based on similarity-preserving overcomplete dictionary is formulated to enhance the global feature consistency, and then an estimated method of neighborhood similarity is presented to guarantee local feature consistency, finally, a global feature patch and local feature patch weighted method are applied to obtain the target patch. Experimental results on damaged murals demonstrate the proposed method outperforms state-of-the-art inpainting methods.

关 键 词：线性系统 敦煌壁画 稀疏表示 图像修复 

分 类 号：TN911.73[电子电信—通信与信息系统]