Performance Analysis of Scalar DC-QIM Forwatermark Detection

Quantization-based schemes, such as scalar DC-QIM, have demonstrated performance merits for data-hiding problem, which is mainly a transmission problem. However, a number of applications are stated in terms of watermark detection problem (also named one-bit watermarking), and this situation has been seldom addressed in the literature for quantization-based techniques. In this context, we carry out a complete performance analysis of uniform quantizers-based schemes with distortion compensation (DC) under additive white Gaussian noise. Implementing an exact Neyman-Pearson test and using large deviation theory, performances are evaluated according to receiver operating characteristic (ROC) and probability of error. Optimal DC's regarding to ROC performances are derived. It is pointed out that false-alarm and miss detection capabilities are jointly optimized by the same DC value. Then, performances are compared with raw quantized-schemes (i.e. without DC) and spread-spectrum (SS) watermarking. It is shown that DC-QIM always outperforms QIM and SS for detection task. The gain provided by the DC reaches several orders of magnitude for cases of interest, that is for low watermark-to-noise regimes. A short comparison is also provided with respect to the corresponding transmission problem, thus evaluating the loss in performance due to the detection

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