测试科学与仪器2010，Vol.1Issue(3)：271-275,5.DOI:10.3969/j.issn.1674-8042.2010.03.15
Performance of Spread Spectrum Watermarking in Autoregressive Host Model Under Additive White Gaussian Noise Channel
Performance of Spread Spectrum Watermarking in Autoregressive Host Model Under Additive White Gaussian Noise Channel
摘要
Abstract
A large class of multimedia and biomedical signals can be modeled as Autoregressive (AR) random processes. Performance of watermarking embedding algorithms utilizing this host model is still left unexplored. The authors investigate the decoding performance of Spread Spectrum (SS) embedding algorithm in the standard Additive White Gaussian Noise (AWGN) channel with the host signal being modeled as AR process. The SS embedding algorithm also use linear interference cancelation in the subspace spanned by watermark pattern. They study the influence of design parameters on the decoding performance. The analytic result is verified by Monte Carlo simulation on synthesized AR process. The result may be helpful to design watermarking system for speech, biomedical and image signals.关键词
spread spectrum watermarking/interference cancelation/AR process/performance analysisKey words
spread spectrum watermarking/interference cancelation/AR process/performance analysis分类
天文与地球科学引用本文复制引用
Bin YAN,Xiao-ming WANG,Yin-jing GUO..Performance of Spread Spectrum Watermarking in Autoregressive Host Model Under Additive White Gaussian Noise Channel[J].测试科学与仪器,2010,1(3):271-275,5.基金项目
This work was supported by research project of "SUST Spring Bud" : the research on decoder under desynchronization attack for data hiding systems. （）
