Saliency-Aware Image Completion

Z. Li, Haoqian Wang, Kai Li
{"title":"Saliency-Aware Image Completion","authors":"Z. Li, Haoqian Wang, Kai Li","doi":"10.1109/CSE.2014.119","DOIUrl":null,"url":null,"abstract":"In this paper, we present a saliency-aware image completion method which takes full advantage of a saliency detection result. On one hand, the saliency map is incorporated into the completion order computation procedure to take human visual attention into account. On the other hand, the saliency map used in patch matching makes the searched result more accurate and smooth. Furthermore, we employ an adaptive patch size determination algorithm which considers the color, structure, and saliency information simultaneously. Experiment results demonstrate the effectiveness of our system in preserving the structural information and robustness in various image content. We also show that the proposed system synthesizes more photo-realistic images than other image completion approaches.","PeriodicalId":258990,"journal":{"name":"2014 IEEE 17th International Conference on Computational Science and Engineering","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE 17th International Conference on Computational Science and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSE.2014.119","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

In this paper, we present a saliency-aware image completion method which takes full advantage of a saliency detection result. On one hand, the saliency map is incorporated into the completion order computation procedure to take human visual attention into account. On the other hand, the saliency map used in patch matching makes the searched result more accurate and smooth. Furthermore, we employ an adaptive patch size determination algorithm which considers the color, structure, and saliency information simultaneously. Experiment results demonstrate the effectiveness of our system in preserving the structural information and robustness in various image content. We also show that the proposed system synthesizes more photo-realistic images than other image completion approaches.
显著性感知图像补全
本文提出了一种充分利用显著性检测结果的显著性感知图像补全方法。一方面,在补全顺序计算过程中引入显著性图,以考虑人的视觉注意;另一方面,在patch匹配中使用的显著性映射使得搜索结果更加准确和平滑。此外,我们还采用了一种同时考虑颜色、结构和显著性信息的自适应补丁大小确定算法。实验结果表明,该系统在保留结构信息和鲁棒性方面是有效的。我们还表明,所提出的系统比其他图像补全方法合成的图像更逼真。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信