Audio Informed Watermarking by means of Dirty Trellis Codes

We present a frequency-domain audio watermarking scheme based on dirty convolutional codes. In the scenario addressed by the paper, a masking threshold is proprely defined to allow the identification of the inaudibility of the inserted data. In particular, the masking threshold defines the maximum modification which can applied to each frequency sample. This represents a major deviation from classical distortion models, in which inaudibility is defined in terms of Mean Square Error (MSE), thus making the direct application of the dirty coding paradigm, derived from a theoretical perspective, problematic. To get around this problem, we first define an informed watermarking scheme based on trellis codes, in which the same information is represented by several paths of the trellis. Then, we determine both the specific structure of the codes and the algorithm for information embedding. The proposed scheme is proved to be robust to D/A and A/D conversion, multipath, scaling, noise, and time misalignment.