Quantization-Based Digital Audio Watermarking in Discrete Fourier Transform Domain

Abstract

To explore the principle and performances of Quantization Index Modulation (QIM) watermarking algorithm, the realization schemes of this algorithm in Discrete Fourier Transform (DFT) domain are classified into three types according to the differences of quantizer parameters, and then the illustrative diagrams of these schemes are given, so the properties of transparency, robustness and capacity of each scheme are concluded. The scheme with best distortion-robustness trade-off is found on that basis. The more efficient embedding and extracting formulas of this scheme are given, and the performances are researched by theoretical analysis rather than computer simulation. The conclusions show that the transparency is in proportion to the square of quantization step and small DFT coefficient leads to poor transparency. The robustness to Additive White Gaussian Noise (AWGN) only relates to the quantization step and the algorithm is susceptible to amplitude scale and resampling attacks. The possible capacity is F_o/2 bits per second, which can satisfy various watermarking applications. To improve the robustness, an adaptive quantization algorithm based on masking properties of the Human Auditory System (HAS) is proposed at the end of this paper, and the algorithm is evaluated in the analog channel environment and its robustness is proved by the results.