Spread Spectrum Watermark Embedder Optimization using Genetic Algorithms

This paper looks Spread Spectrum (SS) watermarking from a different angle where number of cover signal points, payload capacity and watermark signal-to-interference ratio are optimized. The objective is to meet an acceptable BER (bit error rate) and peak-to-average distortion (PAD)on a single point of the cover signal under the constraint of a given embedding distortion and cover size. First, a new model of spread spectrum (SS) watermarking is proposed where each watermark bit is spread using a distinct code pattern over N-mutually orthogonal signal points. Decision variable for each bit of watermark decoding is formed from the weighted average of N-decision statistics. Each watermarked signal point is then modified (attack channel) as Rayleigh distribution followed by AWGN (additive white Gaussian noise). Genetic algorithm (GA) is used to reduce the searching time in this multidimensional nonlinear problem of conflicting nature. Simulation results show that optimizing the number of cover signal points, payload capacity and watermark signal-to-interference ratio (WSIR), better acceptable values of both BER and PAD can be achieved simultaneously.