Blind Detection Techniques For Spread Spectrum Audio Watermarking

Abstract

In spreads pectrum (SS)watermarking of audio signals, since the watermark acts as an additive noise to the host audio signal, the most important challenge is to maintain perceptual transparency. Human perception is a very sensitive apparatus, yet can be exploited to hide some information, reliably. SS watermark embedding has been proposed, in which psycho-acoustically shaped pseudo-random sequences are embedded directly into the time domain audio signal. However, these watermarking schemes use informed detection, in which the original signal is assumed available to the watermark detector. Blind detection of psycho-acoustically shaped SS watermarking is not well addressed in the literature. The problem is still interesting, because, blind detection is more practical for audio signals and, psycho-acoustically shaped watermarks embedding offers the maximum possible watermark energy under requirements of perceptual transparency. In this thesis we study the blind detection of psycho-acoustically shaped SS watermarks in time domain audio signals. We focus on a class of watermark sequences known as random phase watermarks, where the watermark magnitude spectrum is defined by the perceptual criteria and the randomness of the sequence lies in their phase spectrum. Blind watermark detectors, which do not have access to the original host signal, may seem handicapped, because an approximate watermark has to be re-derived from the watermarked signal. Since the comparison of blind detection with fully informed detection is unfair, a hypothetical detection scheme, denoted as semi-blind detection, is used as a reference benchmark. In semi-blind detection, the host signal as such is not available for detection, but it is assumed that sufficient information is available for deriving the exact watermark, which could be embedded in the given signal. Some reduction in performance is anticipated in blind detection over the semi-blind detection. Our experiments revealed that the statistical performance of the blind detector is better than that of the semi-blind detector. We analyze the watermark-to-host correlation (WHC) of random phase watermarks, and the results indicate that WHC is higher when a legitimate watermark is present in the audio signal, which leads to better detection performance. Based on these findings, we attempt to harness this increased correlation in order to further improve the performance. The analysis shows that uniformly distributed phase difference (between the host signal and the watermark) provides maximum advantage. This property is verified through experimentation over a variety of audio signals. In the second part, the correlated nature of audio signals is identified as a potential threat to reliable blind watermark detection, and audio pre-whitening methods are suggested as a possible remedy. A direct deterministic whitening (DDW) scheme is derived, from the frequency domain analysis of the time domain correlation process. Our experimental studies reveal that, the Savitzky-Golay Whitening (SGW), which is otherwise inferior to DDW technique, performs better when the audio signal is predominantly low pass. The novelty of this work lies in exploiting the complementary nature of the two whitening techniques and combining them to obtain a hybrid whitening (HbW) scheme. In the hybrid scheme the DDW and SGW techniques are selectively applied, based on short time spectral characteristics of the audio signal. The hybrid scheme extends the reliability of watermark detection to a wider range of audio signals. We also discuss enhancements to the HbW technique for robustness to temporal offsets and filtering. Robustness of SS watermark blind detection, with hybrid whitening, is determined through a set of experiments and the results are presented. It is seen that the watermarking scheme is robust to common signal processing operations such as additive noise, filtering, lossy compression, etc.