KEYWORDS: Forward error correction, Data hiding, Computer programming, Quantization, Signal to noise ratio, Digital watermarking, Distortion, Data compression, Composites, Bridges
It has recently been discovered that many current applications such as data hiding and watermarking can be posed as the problem of channel coding with side information. As a result there has been considerable interest in designing codes to try and attain the theoretical capacity of the problem. It was shown by Pradhan et. al that in order to achieve capacity, a powerful channel codebook that partitions into a powerful source codebook should be chosen. The data to be embedded will index the source codebook partition. The constructions that exist in the literature, however, are typically based on powerful channel codebooks and weak source codebook partitions and hence remain at a considerable gap to capacity. In this paper, we present several methods of construction that are based on a powerful channel codebook (i.e. turbo codes) and powerful source codebook partitions (i.e., trellis coded quantization) to try and bridge the gap to capacity. For the Gaussian channel coding with side information (CCSI) problem at a transmission rate of 1 bit/channel use, our proposed approach comes within 2.72 dB of the information-theoretic capacity.
Inspired by a recently proposed constructive framework for the distributed source coding problem, we propose a powerful constructive approach to the watermarking problem, emphasizing the dual roles of 'source codes' and 'channel codes.' In our framework, we explore various source and channel codes to achieve watermarks that are robust to attackers in terms of maximizing the distortion between the corrupted coded-source signal and the original signal while holding the distortion between the coded-source signal and the original signal constant. We solve the resulting combinatorial optimization problem using an original technique based on robust optimization and convex programming.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.