Wavelet Domain Audio Watermarking Algorithm Based on Mean Quantization

This article presents a wavelet domain audio watermarking algorithm based on mean quantization. The algorithm supports both watermark embedding and extraction operations while demonstrating strong robustness against common audio processing operations. The implementation involves using wavelet transform to process audio signals, where watermark information is embedded through quantization of specific signal characteristics. The core algorithm operates by first decomposing the audio signal using discrete wavelet transform (DWT) to obtain approximation and detail coefficients. The watermark embedding process typically quantizes the mean values of selected wavelet coefficients according to a predetermined quantization step size, where the quantization direction (up or down) is determined by the binary watermark bits. For extraction, the inverse process detects the quantization patterns to recover the embedded watermark. This technique enables the embedding of specific identifiers in audio files for copyright protection and authenticity verification. The algorithm not only safeguards audio file copyrights but also finds applications in digital watermarking domains such as audio fingerprinting and digital rights management systems. The implementation typically involves key functions including wavelet decomposition, coefficient selection, quantization modulation, and inverse wavelet reconstruction. Therefore, the mean quantization-based wavelet domain audio watermarking algorithm represents a valuable technology that plays a significant role in protecting intellectual property and ensuring file integrity.