一种基于BEMD方法的图像水印算法

Wei Huang, Yan-zhong Sun
{"title":"一种基于BEMD方法的图像水印算法","authors":"Wei Huang, Yan-zhong Sun","doi":"10.1109/ICCCAS.2007.4348123","DOIUrl":null,"url":null,"abstract":"A new image adaptive watermarking algorithm based on Bidimension Empirical Mode Decomposition (BEMD) is proposed. As a new two-dimensional signal processing tool, BEMD is first introduced into the image watermarking field in this paper. In the proposed algorithm, the cover image is decomposed into several intrinsic mode functions (IMFs) based on its local feature adaptively. Then the human visual system (HVS) model function based on IMFs and the logo image is generated, and inserted into the cover image. BEMD technique is used in the extracting processes as well and the recovered watermark image is obtained clearly. We have tested the robustness of the proposed scheme under cropping, JPEG compression, resizing, median filtering, and additive white Gaussian noise (AWGN) attacks. The experiments indicate that this technique can achieve high imperceptibility while showing good robustness. Furthermore, the proposed method is compared with the block DCT based method, and the experiment result confirms that the proposed method shows better performance.","PeriodicalId":218351,"journal":{"name":"2007 International Conference on Communications, Circuits and Systems","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"A New Image Watermarking Algorithm Using BEMD Method\",\"authors\":\"Wei Huang, Yan-zhong Sun\",\"doi\":\"10.1109/ICCCAS.2007.4348123\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A new image adaptive watermarking algorithm based on Bidimension Empirical Mode Decomposition (BEMD) is proposed. As a new two-dimensional signal processing tool, BEMD is first introduced into the image watermarking field in this paper. In the proposed algorithm, the cover image is decomposed into several intrinsic mode functions (IMFs) based on its local feature adaptively. Then the human visual system (HVS) model function based on IMFs and the logo image is generated, and inserted into the cover image. BEMD technique is used in the extracting processes as well and the recovered watermark image is obtained clearly. We have tested the robustness of the proposed scheme under cropping, JPEG compression, resizing, median filtering, and additive white Gaussian noise (AWGN) attacks. The experiments indicate that this technique can achieve high imperceptibility while showing good robustness. Furthermore, the proposed method is compared with the block DCT based method, and the experiment result confirms that the proposed method shows better performance.\",\"PeriodicalId\":218351,\"journal\":{\"name\":\"2007 International Conference on Communications, Circuits and Systems\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-07-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 International Conference on Communications, Circuits and Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCCAS.2007.4348123\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 International Conference on Communications, Circuits and Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCAS.2007.4348123","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

摘要

提出了一种基于二维经验模态分解(BEMD)的图像自适应水印算法。本文首次将BEMD作为一种新的二维信号处理工具引入到图像水印领域。该算法根据图像的局部特征自适应地将图像分解为多个固有模态函数(IMFs)。然后基于IMFs和logo图像生成人类视觉系统(HVS)模型函数,并插入到封面图像中。在提取过程中还采用了BEMD技术,得到了清晰的水印图像。我们已经测试了该方案在裁剪、JPEG压缩、调整大小、中值滤波和加性高斯白噪声(AWGN)攻击下的鲁棒性。实验表明,该方法在具有良好鲁棒性的同时,具有较高的不可感知性。将该方法与基于分块DCT的方法进行了比较,实验结果证实了该方法具有更好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
A New Image Watermarking Algorithm Using BEMD Method
A new image adaptive watermarking algorithm based on Bidimension Empirical Mode Decomposition (BEMD) is proposed. As a new two-dimensional signal processing tool, BEMD is first introduced into the image watermarking field in this paper. In the proposed algorithm, the cover image is decomposed into several intrinsic mode functions (IMFs) based on its local feature adaptively. Then the human visual system (HVS) model function based on IMFs and the logo image is generated, and inserted into the cover image. BEMD technique is used in the extracting processes as well and the recovered watermark image is obtained clearly. We have tested the robustness of the proposed scheme under cropping, JPEG compression, resizing, median filtering, and additive white Gaussian noise (AWGN) attacks. The experiments indicate that this technique can achieve high imperceptibility while showing good robustness. Furthermore, the proposed method is compared with the block DCT based method, and the experiment result confirms that the proposed method shows better performance.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
DC Tolerance Analysis of Nonlinear Circuits Using Set-Valued Functions Mining Co-regulated Genes Using Association Rules Combined with Hash-tree and Genetic Algorithms MTIM for IEEE 802.11 DCF power saving mode The Total Dose Radiation Hardened MOSFET with Good High-temperatue Performance Partner choice based on beam search in wireless cooperative networks
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1