Entropy-Based Audio Watermarking via the Point of View on the Compact Particle Swarm Optimization

This study aims to present an optimization-based audio watermarking using entropy-based watermarking technique in the wavelet domain. In general, the performance of a watermarking system is measured in terms of signal-to-noise ratio (SNR) and bit error rate (BER). However, there is a tradeoff between them which issues a challenge in the field of the watermarking. To overcome this challenge, this study first integrates entropy-based embedding technique and SNR into an optimization problem. Because of uncertain service environment for the audio media, an optimization algorithm with less hardware requirement is required to solve this problem. Since both performance index and constraint are nonlinear, the compact particle swarm optimization (cPSO) which suits for embedded system can do this well. In addition, the hidden information can be extracted without knowledge of the original audio. In the experiments, the performance of the proposed method is tested and the results verify the better SNR and the strong robustness against most signal processing or attacks.