Image-adaptive hidgh-volume data hiding based on scalar quantization

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

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


Information-theoretic analyses for data hiding prescribe embedding 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. The three main findings are as follows: (i) Scalar quantization based data hiding schemes incur a 2 dB penalty from the optimal embedding strategy, which involves vector quantization of the host. (ii) In order to limit perceivable distortion while hiding large amounts of data, hiding schemes must use local perceptual criteria in addition to information-theoretic guidelines. (iii) Powerful erasures and errors correcting codes provide a flexible framework that allows the data-hider freedom of choice of where to embed without requiring synchronization between encoder and decoder.
[PDF] [BibTex]
N. Jacobsen, K. Solanki, U. Madhow, B. S. Manjunath and S. Chandrasekaran,
IEEE Military Communications Conference (MILCOM), vol. 1, pp. 411-415, Anaheim, CA, USA, Oct. 2002.
Node ID: 345 , DB ID: 143 , VRLID: 110 , Lab: VRL , Target: Proceedings
Subject: [Digital Watermarking and Data Hiding] « Look up more