Information Theoretic Bounds For Data Hiding In Compressed Images

We present an information-theoretic approach to obtain an estimate of the number of bits that can be hidden in still images, or, the capacity of the data-hiding channel. We show how addition of the message signal in a suitable transform domain rather than the spatial domain can significantly increase the channel capacity. We compare the capacities achievable with different decompositions like DCT, DFT, Hadamard, and subband transforms. INTRODUCTION Data hiding or Steganography, is a rapidly growing field with potential applications for copyright protection (watermarking), hiding executables for access control of digital multimedia data, embedded captioning, secret communications, etc. It is therefore of significant interest to have a theoretical estimate of the number of bits that can be hidden in multimedia data. In this paper we provide an information-theoretic approach to estimate the number of bits that can be hidden in still images. Let I be the original (cover) image, to which ..

A Robust Scheme For Oblivious Detection Of Watermarks / Data Hiding In Still Images

We propose a novel, robust scheme for data hiding/ oblivious detection of watermarks in still images. While the low-frequency image coefficients are robust, they cannot be used effectively for oblivious detection methods, when correlative processing is employed for detection. However, in the proposed non-linear detection method, the robust low-frequency bands can be used effectively. Thus the proposed method turns out to be more robust than methods employing linear addition and correlative extraction of the signature. We report the results obtained for 7 test images in terms of probability of error in detection of the watermark/ hidden bits

Multiresolution signal decomposition: transforms, subbands, and wavelets

This book provides an in-depth, integrated, and up-to-date exposition of the topic of signal decomposition techniques. Application areas of these techniques include speech and image processing, machine vision, information engineering, High-Definition Television, and telecommunications. The book will serve as the major reference for those entering the field, instructors teaching some or all of the topics in an advanced graduate course and researchers needing to consult an authoritative source.n The first book to give a unified and coherent exposition of multiresolutional signal decompo

Self-Noise Suppression Schemes In Blind Image Steganography

Blind or oblivious data hiding, can be considered as a signaling method where the origin of the signal constellation is not known. The origin however, can be estimated, by means of self-noise suppression techniques. In this paper, we propose such a technique, and present both theoretical and numerical evaluations of its performance in an additive noise scenario. The problem of optimal choice of the parameters of the proposed technique is also explored, and solutions are presented. Though the cover object is assumed to be an image for purposes of illustration, the proposed method is equally applicable for other types of multimedia data, like video, speech or music