文章基本信息

标题：A Concert Evaluation of Exemplar Based Image Inpainting Algorithms for Natural Scene Image Completion
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作者：K.Sangeetha ; P.Sengottuvelan ; E.Balamurugan 等
期刊名称：Computer Science & Information Technology
电子版ISSN：2231-5403
出版年度：2012
卷号：2
期号：4
页码：335-340
DOI：10.5121/csit.2012.2432
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Image inpainting derives from restoration of art works, and has been applied to repair ancient art works. Inpainting is a technique of restoring a partially damaged or occluded image in an undetectable way. It fills the damaged part of an image by employing information of the undamaged part according to some rules to make it look “reasonable” to human eyes. Digital image inpainting is relatively new area of research, but numerous and different approaches to tackle the inpainting problem have been proposed since the concept was first introduced. This paper analyzes and compares the recent exemplar based inpainting algorithms by Minqin Wang and Hao Guo et al. A number of examples on real images are demonstrated to evaluate the results of algorithms using Peak Signal to Noise Ratio (PSNR).
关键词：Exemplar based; Image inpainting; PSNR.