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Improving data hiding by using convolutional codes and soft-decision decoding

This paper presents an other way of considering watermarking methods, which are analyzed from the point of view of the Information Theory. Watermarking is thus a communication problem in which some information bits have to be transmitted through an additive noise channel subjected to distortions and attacks. Designing watermarking methods in such a way that this channel is Gaussian can be profitable. This paper shows to what extent error protection techniques extensively studied for digital communication through Gaussian channels can be used advantageously for watermarking. Convolutional codes combined with soft-decision decoding are the best example. Especially, when soft-decision Viterbi decoding is employed, this kind of coding schemes can achieve much better performance than BCH codes, at comparable levels of complexity and redundancy, both for still and moving images.