基于t-混合模型分割的VQ数字水印算法

B. Luo, Wei Gu, Hui Guo
{"title":"基于t-混合模型分割的VQ数字水印算法","authors":"B. Luo, Wei Gu, Hui Guo","doi":"10.1109/ICNNSP.2008.4590371","DOIUrl":null,"url":null,"abstract":"To improve codebook quality in the process of vector quantization, the paper proposes a novel codebook generation algorithm which is based on image segmentation using t-mixture models and greedy EM algorithm. Additionally, in the initial codebook generating procedure, the PNN algorithm is used to reduce LBG algorithmpsilas sensitivity to initial codebook. Experimental results show that the proposed algorithm not only significantly improves codebook quality, but also preserves most details of the original image. An even more important feature is that the proposed algorithm is robust to common image processing operations such as cropping, sharpening and filtering.","PeriodicalId":250993,"journal":{"name":"2008 International Conference on Neural Networks and Signal Processing","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A VQ digital watermark algorithm based oN t-mixture models segmentation\",\"authors\":\"B. Luo, Wei Gu, Hui Guo\",\"doi\":\"10.1109/ICNNSP.2008.4590371\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To improve codebook quality in the process of vector quantization, the paper proposes a novel codebook generation algorithm which is based on image segmentation using t-mixture models and greedy EM algorithm. Additionally, in the initial codebook generating procedure, the PNN algorithm is used to reduce LBG algorithmpsilas sensitivity to initial codebook. Experimental results show that the proposed algorithm not only significantly improves codebook quality, but also preserves most details of the original image. An even more important feature is that the proposed algorithm is robust to common image processing operations such as cropping, sharpening and filtering.\",\"PeriodicalId\":250993,\"journal\":{\"name\":\"2008 International Conference on Neural Networks and Signal Processing\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-06-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 International Conference on Neural Networks and Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICNNSP.2008.4590371\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 International Conference on Neural Networks and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNNSP.2008.4590371","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

为了提高矢量量化过程中的码本质量,提出了一种基于t混合模型和贪婪EM算法的图像分割的码本生成算法。此外,在初始码本生成过程中,采用PNN算法降低LBG算法对初始码本的敏感性。实验结果表明,该算法不仅显著提高了码本质量,而且保留了原始图像的大部分细节。更重要的是,该算法对常见的图像处理操作(如裁剪、锐化和滤波)具有鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A VQ digital watermark algorithm based oN t-mixture models segmentation
To improve codebook quality in the process of vector quantization, the paper proposes a novel codebook generation algorithm which is based on image segmentation using t-mixture models and greedy EM algorithm. Additionally, in the initial codebook generating procedure, the PNN algorithm is used to reduce LBG algorithmpsilas sensitivity to initial codebook. Experimental results show that the proposed algorithm not only significantly improves codebook quality, but also preserves most details of the original image. An even more important feature is that the proposed algorithm is robust to common image processing operations such as cropping, sharpening and filtering.
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
×
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