Optimum Detection for Spread-Spectrum Watermarking that Employs Self-masking

Digital watermarking is an effective and promising approach to protect intellectual property rights of digital media. Spread spectrum (SS) is one of the most widely used image watermarking schemes. In SS watermarking, the watermark signal is usually modulated by the just-noticeable difference (JND) of the host image. The JND is measured by advanced perceptual models as a non-linear function of local image features. In this paper, the optimum detection scheme for such non-linearly embedded watermarks is addressed. Closed-form detectors are found for arbitrary JND models that exploit the self-masking property of the human visual system.