音頻水印的時頻分析（multimedia）

• 2020 年 2 月 15 日
• 筆記

現有的音頻水印方法通常是單獨處理一個時間或頻率函數的主音頻訊號，而將其考慮在聯合時頻域內則較少受到關注。本文提出了一種基於TF分析的音頻水印框架。該框架在二維TF平面上處理宿主音頻訊號，並在二維TF影像中選擇一系列的修補程式。這些小塊對應於平均能量最小的TF簇，構成水印嵌入的特徵向量。該框架融合了經典的擴頻嵌入方案。攜帶水印的特徵塊只佔用宿主音頻訊號的少量TF區域，從而提高了不可感知性。此外，由於特徵修補程式包含音頻樣本TF表示的鄰域區域，因此可以利用單個修補程式中樣本之間的相關性提高對一系列處理攻擊的魯棒性。通過大量的實驗驗證了該系統的有效性，並與相應的系統進行了比較。這項工作的目的是闡明TF特徵域中音頻水印的概念，這可能會引導我們找到更健壯的水印解決方案來抵禦惡意攻擊。

原文題目：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

原文鏈接：https://arxiv.org/abs/2002.03156