Wavelet-Based Entropy for Digital Audio Watermarking

Unlike traditional entropy in information theory, this work uses the normalized energy instead of probability to obtain a low-frequency amplitude transform (LAT) on coefficients of discrete wavelet transform (DWT). The watermark is embedded based on the properties and characteristics of this transform. Finally, performance of the proposed scheme is assessed by signal-to-watermark (SWR) and bit error rate (BER). Experimental results demonstrate that the embedded data are robust against most signal processing and attacks, such as re-sampling, low-pass filtering, and amplitude-scaling.