Performance analysis of DCT and DWT audio watermarking based on SVD

Watermarking is the process of embedding information into a signal (e.g. audio, video or pictures) in a way that is difficult to remove. In this paper, a high-capacity audio watermarking system is used to embed data and extract them using singular value decomposition (SVD). With the help of SVD-based algorithms and by using lifting wavelet transform (LWT), discrete cosine transform (DCT) and discrete wavelet transform (DWT). DCT-SVD, DWT-SVD, DWT-DCT-SVD, LWT-DCT-SVD techniques are developed. It was observed that by increasing the quantization levels the signal-to-noise ratio (SNR) value decreases exponentially which leads to distortion in the original signal. It is also observed that robustness is also increased by applying different malicious attacks like re-sampling, re-quantization, echo addition, cropping, additive white gaussian noise (AWGN), signal addition and signal subtraction to the embedded signal which doesn't disturb the original signal and the extracted image. The performance of this technique is evaluated using bit error rate (BER), cross-correlation (CC) and SNR.