Paper
21 March 2005 Robustness improvement of known-host-state watermarking using host statistics
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Abstract
In this paper we consider the problem of performance improvement of known-host-state (quantization-based) watermarking methods undergo additive white Gaussian noise (AWGN) and uniform noise attacks. We analyze the underlying assumptions used for design of Dither Modulation (DM) and Distortion Compensated Dither Modulation (DC-DM) methods and question the optimality of high rate uniform quantizer based embedding into real images from the point of view of robustness of these methods to the selected additive attacks in terms of bit error rate probability. Motivated by superior performance of uniform deadzone quantizer (UDQ) over the uniform one in lossy transform based source coding, we propos to replace the latter one by the UDQ in data-hiding set-up designed according to the statistics of the host data that are assumed to be independent identically distributed Laplacian. Based on the suggested modifications we obtained analytical expressions for bit error rate probability analysis of host-statistics-dependent quantization-based watermarking methods in AWGN and uniform noise attacking channels. Experimental results of computer simulations demonstrate significant performance enhancement of the designed modified DM and DC-DM watermarking techniques in comparison to the classically elaborated known-host-state schemes in terms of the selected performance measure.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Oleksiy Koval, Sviatoslav Voloshynovskiy, F. Deguillaume, Fernando Perez-Gonzalez, and Thierry Pun "Robustness improvement of known-host-state watermarking using host statistics", Proc. SPIE 5681, Security, Steganography, and Watermarking of Multimedia Contents VII, (21 March 2005); https://doi.org/10.1117/12.586270
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Cited by 2 scholarly publications.
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KEYWORDS
Digital watermarking

Error analysis

Distortion

Quantization

Modulation

Data compression

Image compression

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