[1]刘琚,孙建德.独立分量分析的图像/视频分析与应用[J].智能系统学报,2011,6(06):495-506.
 LIU Ju,SUN Jiande.Independent component analysisbased image/video analysis and applications[J].CAAI Transactions on Intelligent Systems,2011,6(06):495-506.
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独立分量分析的图像/视频分析与应用(/HTML)
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第6卷
期数:
2011年06期
页码:
495-506
栏目:
出版日期:
2011-12-25

文章信息/Info

Title:
Independent component analysisbased image/video analysis and applications
文章编号:
1673-4785(2011)06-0495-12
作者:
刘琚孙建德
山东大学 信息科学与工程学院,山东 济南 250100
Author(s):
LIU Ju SUN Jiande
School of Information Science and Engineering, Shandong University, Ji’nan 250100, China
关键词:
独立分量分析特征提取视频分析数字水印
Keywords:
independent component analysis feature extraction video analysis digital watermarking
分类号:
TP18;TN911.7
文献标志码:
A
摘要:
随着通信和计算机技术的发展,图像和视频信息的应用越来越多.图像和视频信息分析中的一个重要方法是获得合适的特征来逼近人类视觉特性.独立分量分析是一种新的无监督训练方法,它可以在图像和视频的理解方面很好地与人类视觉相匹配.给出了不同的ICA图像/视频分析模型和基于这些模型的独立特征,对多媒体ICA分析和数字小波分析方法进行了对比,对于不同分析方法的计算机仿真给出了不同模型的独立特征,并且给出了基于这些特征在图像和视频水印方案中的应用.应用实验的仿真结果表明,独立特征对于图像和视频水印性能具有较好的改善作用.
Abstract:
The application of image and video is becoming increasingly popular with the development of computer and communication techniques. One of the important methods applied in image and video information analysis is to obtain suitable features which approach the visual characteristics of humans. Independent component analysis (ICA) is an unsupervised training method which effectively matches human vision with image and video understanding. In this paper, different image/video analysis models of ICA were presented and the independent image/video features based on these models were analyzed. A comparison between multimedia ICA and digital wavelet transform (DWT) was performed. Finally, computer simulation results on various analysis methods were given to show the independent features of different models and their applications in image and video watermarking. The results of the application simulations show that the independent features may make improvements for image and video watermarking. 

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备注/Memo

备注/Memo:
收稿日期: 2011-01-03.
基金项目:国家自然科学基金资助项目(60872024, 61001180, 60970048);高等学校科技创新工程重大项目培育资金资助项目 (708059);山东大学资助创新基金资助项目(2010JC007);教育部博士点专项基金资助项目(新教师项目,200804221023). 
通信作者:刘琚.E-mail:juliu@sdu.edu.cn.
作者简介:
刘琚,男,1965 年生,工学博士,教授、博士生导师.现为山东大学信息科学与工程学院学术委员会副主任,通信工程系主任;中国电子学会高级会员、IEEE 高级会员(Senior Member);国内外期刊International Journal of Swarm Intelligence Research(IJSIR)、《通信学报》和《数据采集与处理》等编委.主要研究方为多媒体信息处理、无线通信中空时信号处理,盲信号处理理论与应用等.参加了国家重点基础研究发展规划(973)项目和欧盟项目等.主持承担了国家自然科学基金、高等学校科技创新工程重大项目培育资金项目等课题10余项.曾获江苏省科技进步一等奖和中国高校自然科学二等奖等,授权发明专利8项,在国内外核心期刊或重要学术会议上发表学术论文200余篇. 
孙建德,男,1978年生.工学博士,副教授.主要研究方向为基于内容的多媒体分析、基于视觉关注模型的图像/视频分析、图像/视频复制检测、多媒体信息隐藏和数字水印、2D-3D视频转换等.主持并参与了国家自然科学基金等课题10余项.在国内外期刊和重要国际学术会议上发表论文30余篇.
更新日期/Last Update: 2012-02-29