独立分量分析的图像/视频分析与应用  

Independent component analysis-based image/video analysis and applications

作　　者：刘琚[1] 孙建德[1] 

机构地区：[1]山东大学信息科学与工程学院,山东济南250100

出　　处：《智能系统学报》2011年第6期495-506,共12页CAAI Transactions on Intelligent Systems

基　　金：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)

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.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.

关 键 词：独立分量分析 特征提取 视频分析 数字水印 

分 类 号：TN911.73[电子电信—通信与信息系统]