Optimum retrieval of watermark from wavelet significant coefficients

Watermark retrieval in wavelet domain has been proved to be more robust from significant coefficients than high absolute coefficients when a single copy of the watermark is embedded in the original data. The highest absolute coefficients refer to the coefficients with the highest absolute values in any selected band and significant coefficients refer to the coefficients with the highest significance factor with respect to their inter-band dependencies in a wavelet transformed image. The watermark energy can be maximised at each of the selected coefficient by quantising it to the maximum allowable level suggested by a human visual system model. However, as the attacks become very severe, a single copy of the watermark is not sufficient for correct retrieval. Hence, the authors propose a method of optimum retrieval of the watermark from multiple embedded copies under very severe attacks. The authors propose to use the Chair-Varshney decision fusion rule to decide each bit in the watermark instead of the majority rule for optimum watermark retrieval. Simulations are performed to show the superiority of the method with different numbers of watermark copies under various attacks. Extensive simulations are carried out to plot the receiver operating characteristics in order to compare the proposed method with the majority rule.