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DSP09-dtcwt-wm Source Code

This is "The Multimedia Signal Processing and Security Lab", short WaveLab, website. We are a research group at the Computer Sciences Department of the University of Salzburg headed by Andreas Uhl. The short name "WaveLab" already indicates that wavelets are among our favorite tools - we have 15 years of experience in this area. Our research is focused on Multimedia Security including Watermarking, Image and Video Compression, Medical Image Classification, and Biometrics.
MATLAB code implementing and testing the blind DT-CWT domain additive spread-spectrum watermark detector proposed in the paper

Roland Kwitt, Peter Meerwald, Andreas Uhl, "Blind DT-CWT Domain Additive Spread-Spectrum Watermark Detection", In Proceedings of the 16th International Conference on Digital Signal Processing, DSP '09, Santorin, Greece, July 5 - 7, 2009

Abstract: In this paper, we adapt two blind detector structures for additive spread-spectrum image watermarking to the host signal characteristics of the Dual-Tree Complex Wavelet Transform (DT-CWT) domain coefficients. The research is motivated by the superior perceptual characteristics of the DT-CWT and its active use in watermarking. To improve the numerous existing watermarking schemes in which the host signal is modeled by a Gaussian distribution, we show that the Generalized Gaussian nature of Dual-Tree detail subband statistics can be exploited for better detector performance. We found that the Rao detector is more practical than the likelihood-ratio test for our detection problem. We experimentally investigate the robustness of the proposed detectors under JPEG and JPEG2000 attacks and assess the perceptual quality of the watermarked images. The results demonstrate that our alterations allow significantly better blind watermark detection performance in the DT-CWT domain than the widely used linear-correlation detector.


Test Images

Dromedary Models

See README for details.

The code is available upon request.

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