音频水印的时频分析（multimedia）

• 2020 年 2 月 15 日
• 筆記

现有的音频水印方法通常是单独处理一个时间或频率函数的主音频信号，而将其考虑在联合时频域内则较少受到关注。本文提出了一种基于TF分析的音频水印框架。该框架在二维TF平面上处理宿主音频信号，并在二维TF图像中选择一系列的补丁。这些小块对应于平均能量最小的TF簇，构成水印嵌入的特征向量。该框架融合了经典的扩频嵌入方案。携带水印的特征块只占用宿主音频信号的少量TF区域，从而提高了不可感知性。此外，由于特征补丁包含音频样本TF表示的邻域区域，因此可以利用单个补丁中样本之间的相关性提高对一系列处理攻击的鲁棒性。通过大量的实验验证了该系统的有效性，并与相应的系统进行了比较。这项工作的目的是阐明TF特征域中音频水印的概念，这可能会引导我们找到更健壮的水印解决方案来抵御恶意攻击。

原文题目：A Time-Frequency Perspective on Audio Watermarking

原文：Existing audio watermarking methods usually treat the host audio signals of a function of time or frequency individually, while considering them in the joint time-frequency (TF) domain has received less attention. This paper proposes an audio watermarking framework from the perspective of TF analysis. The proposed framework treats the host audio signal in the 2-dimensional (2D) TF plane, and selects a series of patches within the 2D TF image. These patches correspond to the TF clusters with minimum averaged energy, and are used to form the feature vectors for watermark embedding. Classical spread spectrum embedding schemes are incorporated in the framework. The feature patches that carry the watermarks only occupy a few TF regions of the host audio signal, thus leading to improved imperceptibility property. In addition, since the feature patches contain a neighborhood area of TF representation of audio samples, the correlations among the samples within a single patch could be exploited for improved robustness against a series of processing attacks. Extensive experiments are carried out to illustrate the effectiveness of the proposed system, as compared to its counterpart systems. The aim of this work is to shed some light on the notion of audio watermarking in TF feature domain, which may potentially lead us to more robust watermarking solutions against malicious attacks.

原文作者：Haijian Zhang

原文链接：https://arxiv.org/abs/2002.03156