Presented here is a description and analysis of the N-point sparse discrete cosine transform (SDCT), where N is a power of two, which retains all of the properties of the parent DCT such as linearity, energy compaction, and having a fast transform implementation, while allowing arbitrarily-many known zeros, i.e., masked elements, in the input. It has application to image and video compression in that arbitrarily shaped regions may be transformed by the two-dimensional (2D) SDCT with approximately the same resulting compression efficiency as the standard 2D DCT applied to square blocks. The solution is based on a systematic application of symmetry and additive symmetry to the input elements. The four- and eight-point solutions are presented first, with emphasis on development of a set of generating matrices, and finally a general N-point solution is described. The 8×8 SDCT was implemented in VP9 and as expected the transform was found to be perfect and also improved compression efficiency for video objects with a known mask.

In this paper we develop an effective method for arbitrary shape coding based on a four-point DCT. The improvements results from two sources: (1) an effective use of the DCT by efficiently inducing zero-valued transform coefficients, and (2) a novel method of ordering the coefficients allowing the decoder to skip the locations of induced zeros. The algorithm is low complexity, as it only requires only arithmetic and shifting operations in the encoder, and shifting and masking operations in the decoder. The performance is comparable to published techniques in the literature, with the added benefit of low complexity and good performance at both high and low bit rates.

Typical video conferencing scenarios bring together individuals from disparate environments. Unless one commits to expensive tele-presence rooms, conferences involving many individuals result in a cacophony of visuals and backgrounds. Ideally one would like to separate participant visuals from their respective environments and render them over visually pleasing backgrounds that enhance immersion for all. Yet available image/video segmentation techniques are limited and result in significant artifacts even with recently popular commodity depth sensors. In this paper we present a technique that accomplishes robust and visually pleasing rendering of segmented participants over adaptively-designed virtual backgrounds. Our method works by determining virtual backgrounds that match and highlight participant visuals and uses directional textures to hide segmentation artifacts due to noisy segmentation boundaries, missing regions, etc. Taking advantage of simple computations and look-up-tables, our work leads to fast, real-time implementations that can run on mobile and other computationally-limited platforms.

Communication has seen enormous advances over the past 100 years including radio, television, mobile phones, video conferencing, and Internet-based voice and video calling. Still, remote communication remains less natural and more fatiguing than face-to-face. The vision of immersive communication is to enable natural experiences and interactions with remote people and environments in ways that suspend disbelief in being there. This paper briefly describes the current state-of-the-art of immersive communication, provides a vision of the future and the associated benefits, and considers the technical challenges in achieving that vision. The attributes of immersive communication are described, together with the frontiers of video and audio for achieving them. We emphasize that the success of these systems must be judged by their impact on the people who use them. Recent high-quality video conferencing systems are beginning to deliver a natural experience-when all participants are in custom-designed studios. Ongoing research aims to extend the experience to a broader range of environments. Augmented reality has the potential to make remote communication even better than being physically present. Future natural and effective immersive experiences will be created by drawing upon intertwined research areas including multimedia signal processing, computer vision, graphics, networking, sensors, displays and sound reproduction systems, haptics, and perceptual modeling and psychophysics.

In this paper, we present the performance analysis of a self-recovery fragile watermarking scheme using block-neighbor- hood tamper characterization. This method uses a pseudorandom sequence to generate the nonlinear block-mapping and employs an optimized neighborhood characterization method to detect the tampering. Performance of the proposed method and its resistance to malicious attacks are analyzed. We also investigate three optimization strategies that will further improve the quality of tamper localization and recovery. Simulation results demonstrate that the proposed method allows image recovery with an acceptable visual quality (peak signal-to-noise ratio (PSNR) as 25 dB) up to 60% tampering.

We propose a correlogram-based time delay estimation method using signals modeled as the output of the cochlea, where the low-level signal processing happens in the human auditory system. With a normalized correlogram that preserves time-delay patterns that are invariant to speech features such as formants, we employ two-dimensional template matching for time-delay estimation. Experimental results show that our method outperforms a traditional correlogram-based method as well as the GCC-PHAT, especially for short analysis windows in a moderately reverberant environment.

This paper presents a system approach to the residual echo suppression (RES) problem in a noisy acoustic environment. We propose a method that takes advantage of our existing robust acoustic echo cancellation system in order to obtain a residual echo estimate that closely resembles the true, noise-free residual echo. To achieve improved RES during strong near-end interference (e.g., double talk), a psychoacoustic postfilter is also used. The simulation results show that our RES based on the system approach outperforms a conventional estimation method. Comparing the postfiltered output to the unprocessed one indicates that our proposed RES approach can raise the PESQ score by more than half a point.

This paper addresses the problem of identifying impairment types that might be present in a speech signal. In particular, three acoustically induced degradation types that occur in teleconference systems are considered: acoustic echo, reverberation, and broadband noise, as well as combinations among them. The proposed system is double-ended (full reference) and is developed using a database of degraded full-band speech signals created according to a model for teleconference systems. A set of features obtained from both the degraded and non-degraded signals is proposed and shown to adequately capture information associated with each degradation type. A random forest classifier and a support vector machine are successfully employed, achieving a classification error below 2%. Such classifiers can be used to select an appropriate quality assessment tool for a given degraded signal.

Arrays with large number of microphones can be very effective on audio processing tasks, like denoising, acoustic echo removal, etc. New microphone technologies enable creating large arrays with very low cost per component, but the system can still be very expensive due to costs of transmitting all signals to a single processor, and the computational resources to process the large amount of data. We show how a massively-parallel signal processing approach can solve the cost issues, when applied to the problem of sound source localization. We consider the case where each microphone is coupled to simple processing circuitry, which have full-bandwidth access to data from a few other microphones, while only shared power and low-bandwidth connections are provided between each microphone and a central processor. We discuss implementation issues, and show experimental results obtained in simulations and in microphone array measurements.

Random linear network coding can be used in peerto- peer networks to increase the efficiency of content distribution and distributed storage. However, these systems are particularly susceptible to Byzantine attacks. We quantify the impact of Byzantine attacks on the coded system by evaluating the probability that a receiver node fails to correctly recover a file. We show that even for a small probability of attack, the system fails with overwhelming probability. We then propose a novel signature scheme that allows packet-level Byzantine detection. This scheme allows one-hop containment of the contamination, and saves bandwidth by allowing nodes to detect and drop the contaminated packets. We compare the net cost of our signature scheme with various other Byzantine schemes, and show that when the probability of Byzantine attacks is high, our scheme is the most bandwidth efficient.

This paper considers a distance metric learning (DML) algorithm for a fingerprinting system, which identifies a query content by finding the fingerprint in the database (DB) that measures the shortest distance to the query fingerprint. For a given training set consisting of original and distorted fingerprints, a distance metric equivalent to the lpnorm of the difference of two linearly projected fingerprints is learned by minimizing the false-positive rate (probability of perceptually dissimilar content to be identified as being similar) for a given false-negative rate (probability of perceptually similar content to be identified as being dissimilar). The learned metric can perform better than the often used lpdistance and improve the robustness against a set of unexpected distortions. In the experiments, the distance metric learned by the proposed algorithm performed better than those metrics learned by well-known DML algorithms for classification.

This paper presents a new approach for voice activity detection (VAD) in videoconferencing applications based only on video information. In the proposed approach, a face detection scheme is applied to locate the face of the participant, and anthropometric measures are used to identify one patch below each eye, as well as a neighborhood around the mouth. The patches below the eyes are used to train a skin color model suited for that specific person, which is then used to identify non-skin pixels in the mouth neighborhood. The number of non-skin pixels is taken as an estimate of the mouth openness, and its evolution across time is explored for VAD.

Modern telepresence systems can deliver multimedia signals of unprecedentedly high quality of experience to the user. Setting and maintaining such services call for reliable and automatic tools for multimedia quality probing, in special those targeted at speech data along the transmission path. Most of the objective methods for sound quality assessment (QA) in the literature are intended for either speech signals of 4- to 8-kHz bandwidth or general audio until 24 kHz, but are not specifically designed for speech at high sampling-rates. This work approaches quality evaluation of full-band (24 kHz) high-quality speech corrupted by echo. A simple metric singled out from a standardized double-ended tool for audio QA is proposed as a solution for the problem at hand. Quality measures from a set of speech stimuli corrupted by echo under controlled conditions were obtained via listening tests to allow calibration and evaluation of the proposed method. Experimental results reveal an overall correlation of 0.94 between objective and subjective scores, even in the presence of moderate additive noise.

In this paper the design of a double-ended (intrusive) diagnostic tool for identifying five types of degradation in audio signals is reported. The impairment types taken into consideration are additive contamination with pink noise, occurrences of signal mutes, distortion by magnitude clipping, and the previous two types mixed with pink noise. As a simple solution to accomplish the established goal, a threshold-based hierarchical classification system is proposed, being completely defined from pre-processing of the input signals, passing through the estimation of a few characteristic features, up to data clustering criteria. Performance evaluation of the classifier is carried out via a validation database containing 60 impaired signals for each type of impairment, with five distinct degradation intensity levels. Considering the types and range of degradation levels considered in this work, excellent results are achieved, scoring above 96% of correctly classified data in the worst case. System performance in identifying mixed impairment types tends to deteriorate as the strength of the noise component increases.

This paper analyzes the ability of several measurements to quantify the reverberation effect in speech signals. We consider an intrusive scheme, in which the clean and reverberated signals are available, allowing one to estimate the corresponding room impulse response (RIR) signal. An artificial neural network (ANN) is trained for all features and used in a regression approach to estimate the human perceptual evaluation in a mean opinion score (MOS) 1–5 scale. Dimensionality reduction approaches are applied to generate a simpler ANN regression, establishing the most representative features for the problem at hand. A correlation level of 85% with subjective test scores was achieved by reducing the input-vector dimension from 10 to 3, including only the features of reverberation time, room spectral variance, and direct-to-reverberant energy ratio.

This paper proposes a video fingerprinting method based on a novel binary fingerprint obtained using a feature selection algorithm called the symmetric pairwise boosting (SPB). The binary fingerprints are obtained by filtering and quantizing perceptually significant features extracted from an input video clip. The SPB algorithm, which is a generalization of the conventional asymmetric pairwise boosting (APB), selects appropriate filters and quantizers from a class of candidate filters and quantizers in such a way that perceptually similar and dissimilar pairs of video clips are correctly classified as matching and non-matching pairs, respectively. The binary form of the novel fingerprint makes it conducive to an efficient database search, and the experimental results show that the proposed method outperforms the APB-based video fingerprinting methods in terms of both robustness and discriminability.

A novel binary audio fingerprint obtained by filtering and then quantizing the spectral centroids is proposed. A feature selection algorithm, coined pairwise boosting (PB), is used to determine the filters and quantizers by casting the fingerprinting problem of identifying a query audio clip into a binary classification problem. The PB algorithm selects the filters and quantizers which lead to accurate classification of matching and nonmatching audio pairs: a matching pair is an audio pair that should be classified as being identical, and a nonmatching pair is a pair that should be classified as being different. By iteratively reducing the classification error of both matching and nonmatching pairs, the PB algorithm improves both the robustness and discriminating ability. In our experiments, the proposed fingerprint outperformed previously reported binary fingerprints in terms of robustness and discriminating ability. In the experiment, we compared the performances of a number of distance measures.

This paper addresses the design of additive fingerprints that are maximally resilient against linear collusion attacks on a focused correlation detector, as defined below. LetNbe the length of the host vector andMlesN+ 1 the number of users. The focused detector performs a correlation test in order to decide whether a user of interest is among the colluders. Both the fingerprint embedder and the colluders are subject to squared-error distortion constraints. We show that simplex fingerprints maximize a geometric figure of merit for this detector. In that sense they outperform orthogonal fingerprints but the advantage vanishes asMrarr infin. They are also optimal in terms of minimizing the probability of error of the focused detector when the attack is a uniform averaging of the marked copies followed by the addition of white Gaussian noise. Reliable detection is guaranteed provided that the number of colludersKLt radic(N). Moreover, we study the probability of error performance of simplex fingerprints for the focused correlation detector when the colluders use nonuniform averaging plus white Gaussian noise attacks.

In this paper we argue that improved interoperability between DRM systems is likely to benefit to all the actors in the content value chain. Moreover, we describe a domain-based approach to DRM interoperability. We discuss in some detail configuration aspects of such interoperable domains, and how they affect certain social aspects such as marriage and divorce. We conclude that interoperable domains offer a much needed flexibility, allowing users to more easily move between vertical silos and offering content owners a more flexible environment for selling content.

Bit extraction is an essential component of an image hashing system. A good bit extraction scheme should preserve the performance achieved at the feature representation level. In other words the robustness discrimination tradeoff measured by ROC analysis should be preserved. This is dependent on several factors such as, the encountered noise and the number of bits that can be extracted per sample. This paper investigates the relationship between these parameters and proposes some theoretical bounds in achieving a good tradeoff. The analysis primarily focuses on the bit extraction method proposed in [1] and its performance is compared with a scalar quantization based hashing method.

This paper constitutes an introduction to the field of quality evaluation of sound (speech and audio) signals. The need for such an assessment is inherent to modern communications: VoIP, mobile phone, or teleconference systems require meaningful measures of performance, which may ultimately assure good service or profitable business. A brief survey on subjective and objective evaluation methods is provided. Recent developments as well as new topics to be investigated are also addressed. Experiments are conducted to illustrate how to validate quality assessment methods.

Shannon wrote in 1948: rdquoThe semantic aspects of communication are irrelevant to the engineering problemrdquo. He demonstrated indeed that the information generated by a source depends only on its statistics and not on the meaning of the source output. The authors derived the fundamental limits for semantic compaction, transmission and compression systems recently. These systems have the property that the codewords are semantic however, i.e. close to the source sequences. In the present article we determine the minimum distortion for semantic partial transmission systems. In these systems only a quantized version of each source source symbol is transmitted to the receiver. It should be noted that our achievability proof is based on weak instead of strong typicality. This is unusual for Gelfand-Pinsker [1980] related setups as e.g. semantic coding and embedding.

The use of Digital Rights Management (DRM) technologies for the enforcement of digital media usage models is currently subject of a heated debate. Consumer organizations (1) and national governments (2) claim that DRM technology inter- feres with basic personal rights, such as the right to make copies for personal use or the right to use content on any platform of choice. This issue has lately gained increased attention by a trend in some European countries to force DRM vendors and online media stores to open up their respective DRM technologies, i.e. make them interoperable. In this paper we present a DRM interoperability framework that allows multiple DRM systems to seamlessly work together while at the same time requiring minimal modification to existing DRMs. We believe that our solution, which is supported by many stakeholders in the world of digital media, is capable of addressing many of the end-user criticisms of DRM technology. Moreover, the proposed solution is sufficiently flexible to support new business models that may be envisioned by the stakeholders in future distribution of digital media.

Semi-fragile authentication schemes are found to be useful to maintain authentication in the event of certain allowed manipulation of source content. This paper focuses on a quantization based algorithm, and extends it to more general uniform quantizers. Earlier work is found to be a special case of our generalized solution which provides more useful guideline when selecting quantizer for this type of authentication. Experimental results verified our analytical conclusion.

Recent research has shown that network coding can be used in content distribution systems to improve the speed of downloads and the robustness of the systems. However, such systems are very vulnerable to attacks by malicious nodes, and we need to have a signature scheme that allows nodes to check the validity of a packet without decoding. In this paper, we propose such a signature scheme for network coding. Our scheme makes use of the linearity property of the packets in a coded system, and allows nodes to check the integrity of the packets received easily. We show that the proposed scheme is secure, and its overhead is negligible for large files.

We consider the problem of estimating the time-difference-of-arrival (TDOA) for audio source localization in noisy environments, defining a framework for statistical analysis in the phase domain which enables more reliable estimates. This is motivated by the fact that with complex sources, noise, and interfering signals, different frequency bands have significantly different signal-to-noise ratios, creating non-uniform distributions of errors in the phase measurements. Through a new method for analysis of the variations of the phase in frequency windows, we first estimate the signal-to-noise ratio for frequency, and then use it in a maximum-likelihood estimation of the time difference of arrival. We show that this corresponds to a generalization of the Phase Transform method (PHAT), and provides a theoretical justification of why it works so well. Numerical results show how the proposed technique compares favorably with PHAT.

This paper proposes a high capacity reversible image watermarking scheme based on integer-to-integer wavelet transforms. The proposed scheme divides an input image into nonoverlapping blocks and embeds a watermark into the high-frequency wavelet coefficients of each block. The conditions to avoid both underflow and overflow in the spatial domain are derived for an arbitrary wavelet and block size. The payload to be embedded includes not only messages but also side information used to reconstruct the exact original image. To minimize the mean-squared distortion between the original and the watermarked images given a payload, the watermark is adaptively embedded into the image. The experimental results show that the proposed scheme achieves higher embedding capacity while maintaining distortion at a lower level than the existing reversible watermarking schemes.

The use of Digital Rights Management (DRM) technologies for the enforcement of digital media usage models is currently subject of a heated debate. Content creators, owners and distributors argue that DRM technologies are needed to protect their Intellectual Property (IP) from unauthorized access. A counter argument from the Information Technology (IT) and Consumer Electronics (CE) industries states that DRM technologies are obstacles to innovation. Academic institutions add to the discussion by claiming that DRM technologies and associated legislation interfere with their academic mission. Yet another point of view is provided by consumer organizations who claim that DRM technology interferes with basic personal rights, such as the right to make back-up copies for personal use. Finally, national governments express concern that the deployment of DRM technology violates open market rules and regulations and is associated with anti-competitive behavior. This last issue has lately gained increased attention in a number of European countries. In this talk we argue that a number of the concern listed above can be resolved by introducing a sufficiently powerful DRM interoperability framework. In particular we discuss the CORAL DRM interoperability framework that allows multiple DRM systems to seamlessly work together while at the same time requiring minimal modification to participating DRM systems. After introducing the problem of DRM interoperability the following topics will be addressed: (1) approaches to DRM interoperability, (2) introduction to the CORAL architecture, (3) building ecosystems on top of Coral, (4) integrating DRM systems into CORAL and (5) deploying CORAL. We end the talk by going back to the initial problem statement, summarizing to what extent CORAL resolves the identified issues and what work remains to be done.

We consider the problem of decision-making under uncertainty with unbounded loss functions. Inspired by PAC learning model, we use a slightly different model that incorporates the notion of side information in a more generic form to make it applicable to a broader class of applications including system identification and parameter estimation. We address sufficient conditions for consistent decision-making as well as exponential convergence behavior. In this regard, besides a requirement on the growth function of the class of loss functions, it suffices to have a dominating function whose Orlicz expectation is uniformly bounded over the probabilistic model. Decay exponent, decay rate, and sample complexity for expected risk minimization decision policy are discussed, as well

Media streaming over the best-effort public Internet has been a focus of research for over a decade. Enterprise or corporate streaming is another area of media streaming that is practically very important and has a different set of challenges and feasible solutions. For example, the quality and reliability requirements for enterprise streaming are much stricter than for typical Internet streaming. Furthermore, in typical enterprise streaming scenarios, a single entity has control over most elements of the system, including the end-points and the infrastructure. This entity has the powerful ability to monitor, adapt, and deploy new infrastructure as necessary. The goal of this paper is to describe enterprise streaming and identify the basic differences between typical Internet streaming and enterprise streaming, and how these differences alter the challenges that must be overcome for enterprise streaming to be successful. Specifically, we examine enterprise streaming media content delivery network design and operation, video conferencing, peer-to-peer networking (P2P), voice over IP (VoIP), and briefly touch upon wireless and security issues

In Bell Syst. Tech. J., 1948, Shannon wrote: "The semantic aspects of communication are irrelevant to the engineering problem." Indeed Shannon demonstrated that the information that is generated by a source depends only on the statistics of the source, and not on the meaning of the source output. By contrast with this we investigate here whether in a compaction system the codewords can be meaningful just like the source output sequences. We require the codeword to be close to the source sequence for some given distortion measure. For so-called semantic compaction systems we determine the fundamental limits for the i.i.d. case. Moreover we consider semantic transmission systems. These systems have the property that the codewords, i.e. the channel input sequences, are close to the source sequence. Finally we investigate semantic compression. A semantic compression system is actually a vector quantizer for which the codeword, i.e. the index to the reproduction vector, resembles the source sequence. Also for semantic transmission and semantic compression we determine the fundamental limits for the i.i.d. case

Peer-to-peer (P2P) networks are generally considered to be free havens for pirated content, in particular with respect to music. We describe a solution for the problem of copyright infringement in P2P networks for music sharing. In particular, we propose a P2P protocol that integrates the functions of identification, tracking, and sharing of music with those of licensing, monitoring, and payment. This highly decentralized music-aware P2P protocol will allow access to large amounts of music of guaranteed quality; it merges in a natural way the policing functions for copyright protection and an efficient music-management infrastructure for the benefit of the user.

At ISMIR 2002 and CBMI 2001, the authors presented a new approach to audio fingerprinting (Haitsma, J. and Kalker, T., Proc. Int. Conf. on Music Information Retrieval, p.107-15, 2002; Haitsma et al., Proc. Int. Workshop on Content-Based Multimedia Indexing, p.117-25, 2001). The proposed scheme, which we refer to as the streaming audio fingerprinting (SAF) system, allows a very efficient database lookup and is also very robust against many different audio processing steps, including low bit rate audio coding, noise addition and amplitude compression. However it is not inherently robust against large linear speed changes (i.e. speed changes larger than 2%) where both the pitch and the tempo change. This is a potential problem, because some radio stations speed up by a few percent. We discuss a modification of the originally proposed fingerprinting algorithm to make it robust against large linear speed changes. The proposed modification has negligible effect on other aspects, such as robustness and reliability.

Affine transformations are a well-known robustness issue in many multimedia fingerprinting systems. Since it is quite easy with modem computers to apply affine transformations to audio, image and video content, there is an obvious necessity for affine trans-formation resilient fingerprinting. In this paper we present a new method for affine transformation resilient fingerprints that is based upon the auto-correlation of the Radon transform, the log map-ping and the Fourier transform. Besides robustness, we also ad-dress other issues such as security, database search efficiency and independence with perceptually different inputs. Experimental re-sults show that the proposed fingerprints are highly robust to affine transformations. 1.

In this paper we study the problem of optimizing the distortion compensation parameter for the scalar Costa scheme, which is a practical version of the class of distortion compensated dither modulation schemes. In the literature, a number of results are known for finding the value of the distortion compensation parameter that maximizes the capacity of the watermarking channel. Instead, in this paper, we look at minimization of the bit error probability as the criterion for determining the optimal value of the distortion compensation parameter. To this end, we derive a model for the bit error probability, which is subsequently approximated and minimized. This is done both for the cases of Gaussian noise and uniform noise. The results match very well with earlier results by Eggers.

In this paper a video watermarking scheme is presented, that is designed for the future digital cinema format, as it will be used on large projector screens in theatres. The watermark is designed such that it has minimal impact on the video quality, but still is detectable after capture with a handheld camera and conversion to, for instance, VHS, CD-Video or DVD format. In order to achieve the severe requirements, concerning visibility and robustness, the proposed watermarking system only exploits the temporal axis. A watermark is inserted by changing the mean of the luminance values of a frame according to the samples of the watermark. Watermark detection is performed by correlating the watermark sequence with extracted mean luminance values of a sequence of frames. A demonstrator, implementing the proposed algorithm, has been built which shows the aforementioned requirements can be met with the proposed scheme.

In this paper we address the usually implicit assumption that digital watermarking has as its main target copyright and copy protection applications. From these target applications a great many conclusions are drawn about the required security of a watermarking system, and in fact, a considerably percentage of the watermarking literature has this very topic as its main focus of attention. In this paper we take a step back, and try to do a more careful analysis of the 'watermarking-is-for-security-applications' paradigm. The intention of this paper is to discuss the meaning of the concept security in the context of watermarking, and try to show that one has to be careful in using analogies from the related field of cryptography.

We consider a digital watermarking application where multiple parties can embed additional information using their watermark embedder. These parties are not supposed to influence each other and each watermark detector needs to be able to decode the information embedded by any of the embedder systems. One approach would be to use a single secret key and to assign part of the payload to identify the particular embedder. However, it is generally accepted that for security reasons, each embedder should better have its own secret key. A major drawback of this last approach is related to the detector implementation complexity, which increases linearly with the number of embedders. It is shown that this drawback can be overcome by changing the key in the watermarking system dependant on features of the incoming signal.

Watermarking is a technique for embedding imperceptible labels in audio/visual content. Important parameters for any watermarking scheme are imperceptibility, robustness, security, payload, error rates and complexity. In the past few years enormous progress has been made with respect to most of these parameters, except maybe for the latter one. We address this topic of complexity by presenting an efficient method for detecting a spatial video watermark directly in an MPEG video stream. The naive approach would be to do a full MPEG decoding and then apply spatial watermark detection. However, such a full decoding approach would imply large memory and processing resources. We show that, at the cost of a slight decrease of performance, large reductions in complexity are possible. More in particular we show how high speed MPEG parsing, high speed inverse DCT processing and motion compensation can be avoided. On a more abstract level, this paper would like to encourage others to give more prominence to embedding and detection complexity as an important parameter in the design of watermarking schemes.

In the European Esprit project VIVA (Visual Identity Verification Auditor) a real-time digital watermarking system for broadcast monitoring has been investigated and implemented. On top of the usual requirements for watermarks, the VIVA watermarking system has to satisfy an additional number of constraints. One of the most important constraints in a broadcast environment is the robustness of the watermark against scaling. This paper describes how robustness against scaling is achieved in the VIVA project. Furthermore, a real-time implementation of the algorithms is discussed. Experimental results prove the effectiveness of the algorithms.

Electronic watermarking is an active area of research with many applications being foreseen. Watermarks may become an essential tool for copy management in future consumer electronic or PC devices. With simple circuits, detection of watermarks after noise addition, MPEG compression, D/A conversion, pixel shifts appears feasible, but detection after transformations, such as cropping and stretching, remains a challenge. We propose a model to evaluate the effect of scaling on the detector reliability and verify it with experiments.

The main objective of the VIVA project (Visual Identity Verification Auditor) is to investigate and demonstrate a professional broadcast surveillance system. Broadcast material is pre-encoded with an invisible and unique watermark identifier. By automatically monitoring television broadcasts and registering which assets have been pre-encoded, a mechanism for IPR protection is provided. The applications of such a system include copyright protection and proof of ownership, verification of commercial transmissions, assessment of sponsorship effectiveness, protection against illegal transmission, statistical data collection and analysis of broadcast content. The watermarking technology is optimised for the high picture quality needed in a broadcast environment. At the same time, the watermark survives signal processing operations which routinely occur in broadcasting systems such as digital to analogue conversion, editing and compression. The monitoring system detects a 36-bit payload every second, which guarantees an operation time of more than 13 years, without recourse to repeat identifiers. The detection algorithm has reasonably low complexity, enabling real time watermark detection for many broadcast channels simultaneously. We report on the first results of a field trial, using a satellite link between Sweden and Belgium, proving the feasibility of the system.

An important aspect of almost every watermarking system is the performance of the method by which watermark patterns are correlated with (derived features of) the suspect content. In the JAWS video watermarking system, developed at Philips Research, correlation is realized by symmetrical phase-only matched filtering. SPOMF detection has experimentally been shown to be an excellent correlation method. In this paper we address the problem of building a theoretical understanding of its performance. Being a non-linear correlation method, analysis of SPOMF detection performance is difficult. This paper is a first attempt to tackle the problem of deriving an analytical relationship between the energy of the embedded watermark and the reliability of detection. The theoretical results are compared with experimental results, and are found to be in good agreement.

The prospect of consumer digital versatile disk (DVD) recorders highlights the challenge of protecting copyrighted video content from piracy. We describe the copy-protection system currently under consideration for DVD. The copy-protection system broadly tries to prevent illicit copies from being made from either the analog or digital I/O channels of DVD recorders. An analog copy-protection system is utilized to protect the NTSC/PAL output channel by preventing copies to VHS. The digital transmission of content is protected by a robust encryption protocol between two communicating devices. Watermarking is used to encode copy-control information retrievable from both digital and analog signals. Hence, such embedded signals avoid the need for metadata to be carried in either the digital or analog domains. Finally, the copy-protection system provides the capability for one-generation copying. We discuss some proposed solutions and some of the implementation issues that are being addressed.

A digital watermark is a perceptually unobtrusive signal embedded in some multimedia asset carrying additional information: e.g. copyright information of a video clip. For nearly all watermarking schemes published so far, detection is based on some form of correlation. We show that the detection reliability can be significantly improved by applying filtering prior to correlation. This improvement is analysed using a theoretical model based on statistical communication and detection theory. Finally, the improvements predicted by the theory are verified in a number of experiments.

A watermark is a perceptually unobtrusive signal embedded in an image, an audio or video clip, or any other other multimedia asset. Its purpose is to be a label which is holographically attached to the content. Moreover, it can only be removed by malicious and deliberate attacks (without a great loss of content quality) if some secret parameter K is known. In contrast, a watermark should be readily detectable by electronic means. This implies that electronic watermark detection is only feasible if the watermark detector is aware of the secret K. In many watermarking business scenarios the watermark detector will be available to the public as a black box D. The following question is therefore justified: can the secret K be deduced from the operation of the black box D? And if yes, what is the complexity of this process? We address these questions for a large class of watermarking schemes.

We study boundary and transition filters in adaptive para-unitary FIR filter banks. In particular we are interested in the design of optimal boundary and transition filters. We show that there exists (i) a very simple procedure to compute non-optimized boundary and transition filters, and (ii) a non-iterative method to refine these non-optimized filters into filters which are optimal in a weighted MSE sense in the Fourier domain. The paper ends with a short discussion on extensions to multiple dimensions.

The Euclidean algorithm is a frequently used tool in the analysis of one-dimensional (1D) multirate systems. This tool is however not available for multidimensional (MD) multirate systems. The authors discus how Groebner basis techniques can fill this gap. After presenting the relevant facts about Groebner bases, they show in a few examples how this technique can contribute to MD multirate systems theory.

Some results for multidimensional m-band bi-orthogonal filter banks are presented. In the first part of the paper the authors introduce the ladder structure as a method for the design and implementation of the aforementioned filter banks. The second part of the paper focuses upon enforcing linear phase (LP) conditions in the context of ladder structures. The formulation of the LP conditions is done with the help of an algebraically oriented method for describing multidimensional filter banks. It is shown that in this notation, ladder structures allow a natural formulation of LP conditions.>

In many hybrid video compression algorithms there is a clear distinction between motion estimation and compensation (MEMC) on the one hand, and transform coding of the residue on the other hand. By translating MEMC into the framework of matching pursuit (MP), we will show that unification of both steps is possible. Moreover, adapting the MP approach to the small size dictionaries involved in MEMC, it is shown that unification may in principle lead to a better performance of hybrid coding schemes. We close with a discussion on the practical obstacles of the technique, and how to avoid them.>