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The authors propose a new paradigm for blind watermark decoding in the presence of de-synchronization attacks. Employing Forney-style factor graphs to model the watermarking system, they cast the blind watermark decoding problem as a probabilistic inference problem on a graph, and solve it via message-passing. They study a wide range of moderate to strong attacks including scaling, amplitude modulation, fractional shift, arbitrary linear and shift-invariant filtering, and block-wise filtering, and show that the graph-based iterative decoders perform almost as well as if they had exact knowledge of the de-synchronization attack parameters.
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