Approaching the capacity limit in image watermarking:: a perspective on coding techniques for data hiding applications

An overview of channel coding techniques for data hiding in still images is presented. Use of codes is helpful in reducing the bit error probability of the decoded hidden information, thus increasing the reliability of the system. First, the data hiding problem is statistically modeled for the spatial and DCT domains. Then, the benefits brought about by channel diversity are discussed and quantified. We show that it is possible to improve on this basic scheme by employing block, convolutional and orthogonal codes, again giving analytical results. It is shown that the use of superimposed pulses does not produce any benefit when applying them to data hiding. The possibility of using codes at the 'sample level' (that is, without repeating every codeword symbol) is introduced and its potential analyzed for both hard- and soft-decision decoding. Concatenated and turbo coding are also discussed as ways of approaching the hidden channel capacity limit for the sample level case. Finally, experimental results supporting our theoretical approach are presented for some cases of interest. (C) 2001 Elsevier Science B.V. All rights reserved.