By Topic

Image adaptive high volume data hiding based on scalar quantization

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Jacobsen, N. ; Dept. of Electr. & Comput. Eng., California Univ., Santa Barbara, CA, USA ; Solanki, K. ; Madhow, U. ; Manjunath, B.S.
more authors

Information-theoretic analysis for data hiding prescribe embedding the hidden data in the choice of quantizer for the host data. 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 about 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 erasure and error 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.

Published in:

MILCOM 2002. Proceedings  (Volume:1 )

Date of Conference:

7-10 Oct. 2002