摘要
基于对音频特征的分析,提出了一种多小波域的水印算法.结合人类听觉系统的时频掩蔽特性,该算法分析音频帧的过零率及时域能量,确定用于嵌入水印的帧.利用音频的分抽样特征和多小波变换在信号处理中的优势,将每一个音频帧进行分抽样为两个子音频帧并分别将其变换到多小波域.利用两个子音频帧在多小波域的能量来估计所嵌入水印的容量,并根据它们的能量大小关系完成水印的嵌入.水印的提取过程转为一个使用支持向量机进行处理的二分类问题.实验结果验证了所提出的水印算法能根椐音频自身的特点寻找到适合用于嵌入水印的音频帧,且能动态调整水印的嵌入强度,在保证听觉质量的同时提高了水印的鲁棒性.
Based on the analysis of the audio features, a new audio watermarking algorithm using the discrete multiwavelet transform is proposed. Combined with time-frequency masking property of the human auditory system, the proposed algorithm analyses the zero-cross ratio and the short-time energy of each audio frame to choose the audio frames to embed the watermark. Using the features of sub-sampling and the advantages of multiwavelet in signal processing, each frame to embed the watermark is sub-sampled into two sub-audio frames, and these sub-audio frames are decomposed into muhiwa domain, embeddi retrleva velet domain respectively. According to the energies of two sub-audio frames in multiwavelet the capacity of embedded watermark in audio signal is estimated, and then watermark ng is accomplished based on the energy relationship between two sub-audio frames. The embedded watermark can be considered as a classification problem with two-class that can be solved by support vector machines. The experimental results show that the proposed algorithm can find the suitable audio frames to embed watermark according to the features of the audio signal and can also adjust the embedding strength dynamically improving the robustness of watermarking system without losing auditory quality.
出处
《计算机研究与发展》
EI
CSCD
北大核心
2010年第2期216-222,共7页
Journal of Computer Research and Development
基金
四川省教育厅重点项目(2007ZA112)
四川省学术和技术带头人培养基金项目(08209057)
西华大学重点项目(ZG0722603)~~
关键词
数字水印
音频水印
多小波域
支持向量机
音频特征
digital watermarking
audio watermarking
multiwavelet domain
support vector machine
audio feature
