Selection of the optimal embedding positions of digital audio watermarking in wavelet domain

TL;DR

This paper analyzes optimal embedding positions for digital audio watermarking in the wavelet domain, proposing a self-adaptive interpolation algorithm that improves imperceptibility and robustness over traditional methods.

Contribution

It introduces a self-adaptive interpolation embedding algorithm and identifies the best wavelet transform levels for watermark embedding based on experimental analysis.

Findings

Embedding in the first four wavelet levels yields better imperceptibility.

The proposed algorithm outperforms traditional coefficient replacement methods.

Optimal embedding positions vary for different application requirements.

Abstract

This work studied embedding positions of digital audio watermarking in wavelet domain, to make beginners understand the nature of watermarking in a short time. Based on the theory of wavelet transform, this paper analyzed statistical distributions of each level after transformation and the features of watermark embedded in different transform levels. Through comparison and analysis, we found that watermark was suitable for embedding into the coefficients of the first four levels of wavelet transform. In current state-of-art approaches, the embedding algorithms were always to replace the coefficient values of the embedded positions. In contrast this paper proposed an embedding algorithm of selfadaptive interpolation to achieve a better imperceptibility. In order to reduce the computational complexity, we took a pseudo random sequence with a length of 31 bits as the watermark. In the experiments, watermark was embedded in different locations, including different transform levels, high-frequency coefficients and low-frequency coefficients, high-energy regions and low-frequency regions. Results showed that the imperceptibility was better than traditional embedding algorithms. The bit error rates of the extracted watermark were calculated and we analyzed the robustness and fragility of each embedded signal. At last we concluded the best embedding positions of watermark for different applications and our future work.