High-volume data hiding in images: Introducing perceptual criteria into quantization based embedding

K. Solanki, N. Jacobsen, S. Chandrasekaran, U. Madhow, and B. S. Manjunath

Dept. of Electrical and Computer Engineering
University of California at Santa Barbara,
Santa Barbara, CA 93106


Information-theoretic analyses for data hiding prescribe em-bedding the hidden data in the choice of quantizer for the host data. In this paper, we consider a suboptimal implementation of this prescription, with a view to hiding high volumes of data in images with low perceptual degradation. Our two main findings are as follows: (a) In order to limit perceptual distortion while hiding large amounts of data, the hiding scheme must use perceptual criteria in addition to information-theoretic guidelines. (b) By focusing on "benign" JPEG compression attacks, we are able to attain very high volumes of embedded data, comparable to information-theoretic capacity estimates for the more malicious Additive White Gaussian Noise (AWGN) attack channel, using relatively simple embedding techniques.
[PDF] [BibTex]
K. Solanki, N. Jacobsen, S. Chandrasekaran, U. Madhow, and B. S. Manjunath,
ICASSP, vol. 4, pp. 3485-3488, May. 2002.
Node ID: 346 , DB ID: 144 , VRLID: 96 , Lab: VRL , Target: Proceedings
Subject: [Digital Watermarking and Data Hiding] « Look up more