Paper
22 June 2004 Vector-quantization-based scheme for data embedding for images
Author Affiliations +
Abstract
Today, data hiding has become more and more important in a variety of applications including security. Since Costa's work in the context of communication, the set of quantization based schemes have been proposed as one class of data hiding schemes. Most of these schemes are based on uniform scalar quantizer, which is optimal only if the host signal is uniformly distributed. In this paper, we propose pdf -matched embedding schemes, which not only consider pdf -matched quantizers, but also extend them to multiple dimensions. Specifically, our contributions to this paper are: We propose a pdf-matched embedding (PME) scheme by generalizing the probability distribution of host image and then constructing a pdf-matched quantizer as the starting point. We show experimentally that the proposed pdf-matched quantizer provides better trade-offs between distortion caused by embedding, the robustness to attacks and the embedding capacity. We extend our algorithm to embed a vector of bits in a host signal vector. We show by experiments that our scheme can be closer to the data hiding capacity by embedding larger dimension bit vectors in larger dimension VQs. Two enhancements have been proposed to our method: by vector flipping and by using distortion compensation (DC-PME), that serve to further decrease the embedding distortion. For the 1-D case, the PME scheme shows a 1 dB improvement over the QIM method in a robustness-distortion sense, while DC-PME is 1 dB better than DC-QIM and the 4-D vector quantizer based PME scheme performs about 3 dB better than the 1-D PME.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ning Liu and Koduvayur P. Subbalakshmi "Vector-quantization-based scheme for data embedding for images", Proc. SPIE 5306, Security, Steganography, and Watermarking of Multimedia Contents VI, (22 June 2004); https://doi.org/10.1117/12.527219
Lens.org Logo
CITATIONS
Cited by 1 scholarly publication.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Data hiding

Distortion

Digital watermarking

Binary data

Quantization

Signal to noise ratio

Computer programming

RELATED CONTENT

TCQ-based quantizer design for data hiding in images
Proceedings of SPIE (March 21 2005)
Provably robust digital watermarking
Proceedings of SPIE (November 22 1999)
Applied public-key steganography
Proceedings of SPIE (April 29 2002)

Back to Top