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Quantization Index Modulation: A Class of Provably Good Methods for Digital Watermarking and Information Embedding
 IEEE TRANS. ON INFORMATION THEORY
, 1999
"... We consider the problem of embedding one signal (e.g., a digital watermark), within another "host" signal to form a third, "composite" signal. The embedding is designed to achieve efficient tradeoffs among the three conflicting goals of maximizing informationembedding rate, mini ..."
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Cited by 465 (13 self)
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We consider the problem of embedding one signal (e.g., a digital watermark), within another "host" signal to form a third, "composite" signal. The embedding is designed to achieve efficient tradeoffs among the three conflicting goals of maximizing informationembedding rate, minimizing distortion between the host signal and composite signal, and maximizing the robustness of the embedding. We introduce new classes of embedding methods, termed quantization index modulation (QIM) and distortioncompensated QIM (DCQIM), and develop convenient realizations in the form of what we refer to as dither modulation. Using deterministic models to evaluate digital watermarking methods, we show that QIM is "provably good" against arbitrary bounded and fully informed attacks, which arise in several copyright applications, and in particular, it achieves provably better rate distortionrobustness tradeoffs than currently popular spreadspectrum and lowbit(s) modulation methods. Furthermore, we show that for some important classes of probabilistic models, DCQIM is optimal (capacityachieving) and regular QIM is nearoptimal. These include both additive white Gaussian noise (AWGN) channels, which may be good models for hybrid transmission applications such as digital audio broadcasting, and meansquareerrorconstrained attack channels that model privatekey watermarking applications.
Nested Linear/Lattice Codes for Structured Multiterminal Binning
, 2002
"... Network information theory promises high gains over simple pointtopoint communication techniques, at the cost of higher complexity. However, lack of structured coding schemes limited the practical application of these concepts so far. One of the basic elements of a network code is the binning sch ..."
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Cited by 296 (13 self)
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Network information theory promises high gains over simple pointtopoint communication techniques, at the cost of higher complexity. However, lack of structured coding schemes limited the practical application of these concepts so far. One of the basic elements of a network code is the binning scheme. Wyner and other researchers proposed various forms of coset codes for efficient binning, yet these schemes were applicable only for lossless source (or noiseless channel) network coding. To extend the algebraic binning approach to lossy source (or noisy channel) network coding, recent work proposed the idea of nested codes, or more specifically, nested paritycheck codes for the binary case and nested lattices in the continuous case. These ideas connect network information theory with the rich areas of linear codes and lattice codes, and have strong potential for practical applications. We review these recent developments and explore their tight relation to concepts such as combined shaping and precoding, coding for memories with defects, and digital watermarking. We also propose a few novel applications adhering to a unified approach.
Distributed video coding
 PROC. OF THE IEEE 93 (2005) 71–83
, 2005
"... Distributed coding is a new paradigm for video compression, ..."
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Cited by 283 (11 self)
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Distributed coding is a new paradigm for video compression,
Informationtheoretic analysis of information hiding
 IEEE Transactions on Information Theory
, 2003
"... Abstract—An informationtheoretic analysis of information hiding is presented in this paper, forming the theoretical basis for design of informationhiding systems. Information hiding is an emerging research area which encompasses applications such as copyright protection for digital media, watermar ..."
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Cited by 253 (18 self)
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Abstract—An informationtheoretic analysis of information hiding is presented in this paper, forming the theoretical basis for design of informationhiding systems. Information hiding is an emerging research area which encompasses applications such as copyright protection for digital media, watermarking, fingerprinting, steganography, and data embedding. In these applications, information is hidden within a host data set and is to be reliably communicated to a receiver. The host data set is intentionally corrupted, but in a covert way, designed to be imperceptible to a casual analysis. Next, an attacker may seek to destroy this hidden information, and for this purpose, introduce additional distortion to the data set. Side information (in the form of cryptographic keys and/or information about the host signal) may be available to the information hider and to the decoder. We formalize these notions and evaluate the hiding capacity, which upperbounds the rates of reliable transmission and quantifies the fundamental tradeoff between three quantities: the achievable informationhiding rates and the allowed distortion levels for the information hider and the attacker. The hiding capacity is the value of a game between the information hider and the attacker. The optimal attack strategy is the solution of a particular ratedistortion problem, and the optimal hiding strategy is the solution to a channelcoding problem. The hiding capacity is derived by extending the Gel’fand–Pinsker theory of communication with side information at the encoder. The extensions include the presence of distortion constraints, side information at the decoder, and unknown communication channel. Explicit formulas for capacity are given in several cases, including Bernoulli and Gaussian problems, as well as the important special case of small distortions. In some cases, including the last two above, the hiding capacity is the same whether or not the decoder knows the host data set. It is shown that many existing informationhiding systems in the literature operate far below capacity. Index Terms—Channel capacity, cryptography, fingerprinting, game theory, information hiding, network information theory,
Distributed source coding for sensor networks
 In IEEE Signal Processing Magazine
, 2004
"... n recent years, sensor research has been undergoing a quiet revolution, promising to have a significant impact throughout society that could quite possibly dwarf previous milestones in the information revolution. MIT Technology Review ranked wireless sensor networks that consist of many tiny, low ..."
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Cited by 188 (2 self)
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n recent years, sensor research has been undergoing a quiet revolution, promising to have a significant impact throughout society that could quite possibly dwarf previous milestones in the information revolution. MIT Technology Review ranked wireless sensor networks that consist of many tiny, lowpower and cheap wireless sensors as the number one emerging technology. Unlike PCs or the Internet, which are designed to support all types of applications, sensor networks are usually mission driven and application specific (be it detection of biological agents and toxic chemicals; environmental measurement of temperature, pressure and vibration; or realtime area video surveillance). Thus they must operate under a set of unique constraints and requirements. For example, in contrast to many other wireless devices (e.g., cellular phones, PDAs, and laptops), in which energy can be recharged from time to time, the energy provisioned for a wireless sensor node is not expected to be renewed throughout its mission. The limited amount of energy available to wireless sensors has a significant impact on all aspects of a wireless sensor network, from the amount of information that the node can process, to the volume of wireless communication it can carry across large distances. Realizing the great promise of sensor networks requires more than a mere advance in individual technologies; it relies on many components working together in an efficient, unattended, comprehensible, and trustworthy manner. One of the enabling technologies for sensor networks is distributed source coding (DSC), which refers to the compression of multiple correlated sensor outputs [1]–[4] that do not communicate with each other (hence distributed coding). These sensors send their compressed outputs to a central point [e.g., the base station (BS)] for joint decoding. I
The Gaussian Watermarking Game
, 2000
"... Watermarking models a copyright protection mechanism where an original source sequence or "covertext" is modified before distribution to the public in order to embed some extra information. The embedding should be transparent (i.e., the modified data sequence or "stegotext" shoul ..."
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Cited by 132 (9 self)
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Watermarking models a copyright protection mechanism where an original source sequence or "covertext" is modified before distribution to the public in order to embed some extra information. The embedding should be transparent (i.e., the modified data sequence or "stegotext" should be similar to the covertext) and robust (i.e., the extra information should be recoverable even if the stegotext is modified further, possibly by a malicious "attacker"). We compute the coding capacity of the watermarking game for a Gaussian covertext and squarederror distortions. Both the public version of the game (covertext known to neither attacker nor decoder) and the private version of the game (covertext unknown to attacker but known to decoder) are treated. While the capacity of the former cannot, of course, exceed the capacity of the latter, we show that the two are, in fact, identical. These capacities depend critically on whether the distortion constraints are required to be met in expectation or with probability one. In the former case the coding capacity is zero, whereas in the latter it coincides with the value of related zerosum dynamic mutual informations games of complete and perfect information. # Parts of this work were presented at the 2000 Conference on Information Sciences and Systems (CISS '00), Princeton University, Princeton, NJ, March 1517, 2000, and at the 2000 IEEE International Symposium on Information Theory (ISIT '00), Sorrento, Italy, June 2530, 2000.
Duality between channel capacity and rate distortion with twosided state information
 IEEE TRANS. INFORM. THEORY
, 2002
"... We show that the duality between channel capacity and data compression is retained when state information is available to the sender, to the receiver, to both, or to neither. We present a unified theory for eight special cases of channel capacity and rate distortion with state information, which al ..."
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Cited by 83 (3 self)
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We show that the duality between channel capacity and data compression is retained when state information is available to the sender, to the receiver, to both, or to neither. We present a unified theory for eight special cases of channel capacity and rate distortion with state information, which also extends existing results to arbitrary pairs of independent and identically distributed (i.i.d.) correlated state information @ I PA available at the sender and at the receiver, respectively. In particular, the resulting general formula for channel capacity a �— � @ A ‘ @ Y P A @ Y IA “ assumes the same form as the generalized Wyner–Ziv rate distortion function @ A a �� � @ A @ ” A ‘ @ Y I A @ Y PA“.
Polar Codes are Optimal for Lossy Source Coding
"... Abstract — We consider lossy source compression of a binary symmetric source with Hamming distortion function. We show that polar codes combined with a lowcomplexity successive cancellation encoding algorithm achieve the ratedistortion bound. The complexity of both the encoding and the decoding al ..."
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Cited by 60 (1 self)
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Abstract — We consider lossy source compression of a binary symmetric source with Hamming distortion function. We show that polar codes combined with a lowcomplexity successive cancellation encoding algorithm achieve the ratedistortion bound. The complexity of both the encoding and the decoding algorithm is O(N log(N)), where N is the blocklength of the code. Our result mirrors Arıkan’s capacity achieving polar code construction for channel coding. I.
DataHiding Codes
 Proc. IEEE
, 2005
"... This tutorial paper reviews the theory and design of codes for hiding or embedding information in signals such as images, video, audio, graphics, and text. Such codes have also been called watermarking codes; they can be used in a variety of applications, including copyright protection for digital m ..."
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Cited by 48 (4 self)
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This tutorial paper reviews the theory and design of codes for hiding or embedding information in signals such as images, video, audio, graphics, and text. Such codes have also been called watermarking codes; they can be used in a variety of applications, including copyright protection for digital media, content authentication, media forensics, data binding, and covert communications. Some of these applications imply the presence of an adversary attempting to disrupt the transmission of information to the receiver; other applications involve a noisy, generally unknown, communication channel. Our focus is on the mathematical models, fundamental principles, and code design techniques that are applicable to data hiding. The approach draws from basic concepts in information theory, coding theory, game theory, and signal processing, and is illustrated with applications to the problem of hiding data in images. Keywords—Coding theory, data hiding, game theory, image processing, information theory, security, signal processing, watermarking. I.
Quantization index modulation methods for digital watermarking and information embedding of multimedia. The
 Journal of VLSI Signal Processing
, 2001
"... Abstract. Copyright notification and enforcement, authentication, covert communication, and hybrid transmission applications such as digital audio broadcasting are examples of emerging multimedia applications for digital watermarking and information embedding methods, methods for embedding one signa ..."
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Cited by 42 (3 self)
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Abstract. Copyright notification and enforcement, authentication, covert communication, and hybrid transmission applications such as digital audio broadcasting are examples of emerging multimedia applications for digital watermarking and information embedding methods, methods for embedding one signal (e.g., the digital watermark) within another “host ” signal to form a third, “composite ” signal. The embedding is designed to achieve efficient tradeoffs among the three conflicting goals of maximizing informationembedding rate, minimizing distortion between the host signal and composite signal, and maximizing the robustness of the embedding. We present a class of embedding methods called quantization index modulation (QIM) that achieve provably good ratedistortionrobustness performance. These methods, and lowcomplexity realizations of them called dither modulation, are provably better than both previously proposed linear methods of spread spectrum and nonlinear methods of lowbit(s) modulation against squareerror distortionconstrained intentional attacks. We also derive informationembedding capacities for the case of a colored Gaussian host signal and additive colored Gaussian noise attacks. These results imply an information embedding capacity of about 1/3 b/s of embedded digital rate for every Hertz of host signal bandwidth and every dB drop in received host signal quality. We show that QIM methods achieve performance within 1.6 dB of capacity, and we introduce a form of postprocessing we refer to as distortion compensation that, when combined with QIM, allows capacity to be achieved.