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Abstract

Watermark data is encoded in a digitized signal by forming a noise threshold spectrum which represents a maximum amount of imperceptible noise, spread-spectrum chipping the noise threshold spectrum with a relatively endless stream of pseudo-random bits to form a basis signal, dividing the basis signal into segments, and filtering the segments to smooth segment boundaries. The data encoded in the watermark signal is precoded to make the watermark data inversion robust and is convolutional encoded to further increase the likelihood that the watermark data will subsequently be retrievable notwithstanding lossy processing of the watermarked signal. The basis signal fits noise thresholds determined by constant-quality quantization approximation. Noise introduced by quantization is estimated by determining a continuously differentiable function which approximates noise introduced by such quantization and using the function to solve for a relatively optimal gain to be applied during such quantization. The continuously differentiable function includes a local quantization stepsize. A local quantization stepsize is determined by first determining widths of quantization steps at respective particular amplitudes and interpolating stepssizes for amplitudes between the particular amplitudes. The interpolation of stepsizes provides a smooth function. The continuously differentiable function based upon a local, interpolated quantization stepsize provides an estimation of quantization error which lends itself to efficient and convenient mathematical manipulation.

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First Claim