Diversity assisted GCIC for spread spectrum watermark detection using genetic algorithms

This paper proposes an improved detection algorithm for spread spectrum watermark through the realization of an efficient group combined interference cancellation (GCIC) technique. First, each watermark bit is spread over N-mutually distinct points of the cover signal and the decision variable at the decoder is formed from the weighted average of N-decision statistics. Attack channel is modeled as Rayleigh distribution followed by AWGN (additive white Gaussian noise). Diversity technique is then applied to form the resultant watermarked image from the weighted average of multiple copies in order to improve detection performance where WSIR (watermark signal to interference ratio) is used as weight factor to achieve low BER (bit error rate). Genetic algorithms (GA) is used to partition embedded bits into multiple groups, namely very strong, strong, weak and very weak based on the normalized magnitudes of their decision variables. Performance of the GA based multiple group combined interference cancellation (MGCIC) for four, three and two groups with conventional interference cancellation (IC) are then reported. A significant improvement in detection performance and capacity is seen with GA based group combined interference cancellation (GCIC) relative to conventional interference cancellation (IC) at the cost of slight increase in computation complexity. Simulation results show that bit error rate (BER) for watermark decoding is reduced as the embedded bits are divided into more number of groups and optimal partitioning of these groups are made through the use of GA.