Coding at the sample level for data hiding: turbo and concatenated codes

The performance of data hiding techniques in still images may be greatly improved by means of coding. In previous approaches repetition coding was firstly used to obtain N identical Gaussian channels over which block and convolutional coding were used. But knowing that repetition coding can be improved we may turn our attention to coding forwardly at the sample level. Bounds for both hard and soft decision decoding performance are provided and the use of concatenated coding and turbo coding for this approach is explored.

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