217 research outputs found
Converse bounds on modulation-Estimation performance for the Gaussian multiple-access channel
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Fast Inverse Motion Compensation Algorithms for MPEG-2 and for Partial DCT Information
No full textIn prior work, we developed a fast inverse motion compensation method that can be implemented directly on the DCT domain representation derived from the compressed bitstreams conforming to MPEG, H.261 and H.263 standards. That work was restricted to compressed-domain representations wherein the motion-vectors have integer pel accuracy. Here, we extend this work to sub-pel accurate motion-vectors. Here we also extend the prior work to speedup the inverse motion compensation process in the DCT domain by explicitly exploiting the sparseness of the DCT domain representation. Using partial DCT information we show that the DCT domain method has substantially lower operation count than the conventional spatial domain approach which requires decompression followed by inverse motion-compensation. On sabbatical leave at HP Laboratories. Current address: Hewlett-Packard Laboratories, 1501 Page Mill Road, Palo Alto, CA 94304, U.S.A. Email: [email protected]. Permanent address: HP Israel Science ..
Fast DCT Domain Filtering Using the DCT and the DST
No full textA method for efficient spatial domain filtering, directly in the DCT-IIe domain, is developed and proposed. It consists of using the discrete sine transform (DST), together with the discrete cosine transform (DCT), for transform domain processing, based on the recently derived convolution-multiplication properties of discrete trigonometric transforms. The proposed scheme requires no zero padding of the input data, or kernel symmetry. It is demonstrated that, in typical applications, the proposed algorithm is significantly more efficient than the conventional spatial domain method. The method is applicable to any DCT based data compression standard, such as JPEG, MPEG, and H.261. Keywords: DCT-domain filtering, discrete sine transform, data compression. While on sabbatical leave at Hewlett-Packard Laboratories, 1501 Page Mill Road, Palo Alto, CA 94304, USA. y Address: HP Israel Science Center, Technion City, Haifa 32000, Israel. E-mail: [renato,merhav]@hp.technion.ac.il 1 Introduc..
Lower bounds on joint modulation-estimation performance for the Gaussian MAC
No full textInternational audienceThis paper considers the problem of jointly estimating two independent continuous-valued parameters sent over a Gaussian multiple-access channel (MAC) subject to the mean square error (MSE) as a fidelity criterion. We generalize the parameter modulation-estimation analysis techniques proposed by Merhav in 2012 to a two-user multiple-access channel model to obtain outer bounds to the achievable region in the plane of the MSE's of the two user parameters, as well as the achievable region of the exponential decay rates of these MSE's in the asymptotic regime of long blocks
Stochastic Image Warping for Improved Watermark Desynchronization
No full textThe use of digital watermarking in real applications is impeded by the weakness of current available algorithms against signal processing manipulations leading to the desynchronization of the watermark embedder and detector. For this reason, the problem of watermarking under geometric attacks has received considerable attention throughout recent years. Despite their importance, only few classes of geometric attacks are considered in the literature, most of which consist of global geometric attacks. The random bending attack contained in the Stirmark benchmark software is the most popular example of a local geometric transformation. In this paper, we introduce two new classes of local desynchronization attacks (DAs). The effectiveness of the new classes of DAs is evaluated from different perspectives including perceptual intrusiveness and desynchronization efficacy. This can be seen as an initial effort towards the characterization of the whole class of perceptually admissible DAs, a necessary step for the theoretical analysis of the ultimate performance reachable in the presence of watermark desynchronization and for the development of a new class of watermarking algorithms that can efficiently cope with them
Detection Games under Fully Active Adversaries
No full textWe study a binary hypothesis testing problem in which a defender must decide whether a test sequence has been drawn from a given memoryless source P 0 , while an attacker strives to impede the correct detection. With respect to previous works, the adversarial setup addressed in this paper considers an attacker who is active under both hypotheses, namely, a fully active attacker, as opposed to a partially active attacker who is active under one hypothesis only. In the fully active setup, the attacker distorts sequences drawn both from P 0 and from an alternative memoryless source P 1 , up to a certain distortion level, which is possibly different under the two hypotheses, to maximize the confusion in distinguishing between the two sources, i.e., to induce both false positive and false negative errors at the detector, also referred to as the defender. We model the defender–attacker interaction as a game and study two versions of this game, the Neyman–Pearson game and the Bayesian game. Our main result is in the characterization of an attack strategy that is asymptotically both dominant (i.e., optimal no matter what the defender’s strategy is) and universal, i.e., independent of P 0 and P 1 . From the analysis of the equilibrium payoff, we also derive the best achievable performance of the defender, by relaxing the requirement on the exponential decay rate of the false positive error probability in the Neyman–Pearson setup and the tradeoff between the error exponents in the Bayesian setup. Such analysis permits characterizing the conditions for the distinguishability of the two sources given the distortion levels
Detection Games with a Fully Active Attacker
No full textWe analyze a binary hypothesis testing problem in which a defender has to decide whether or not a test sequence has been drawn from a given source P0 whereas, an attacker strives to impede the correct detection. In contrast to previous works, the adversarial setup addressed in this paper considers a fully active attacker, i.e. the attacker is active under both hypotheses. Specifically, the goal of the attacker is to distort the given sequence, no matter whether it has emerged from P0 or not, to confuse the defender and induce a wrong decision. We formulate the defender-attacker interaction as a game and study two versions of the game, corresponding to two different setups: a Neyman-Pearson setup and a Bayesian one. By focusing on asymptotic versions of the games, we show that there exists an attacking strategy that is both dominant (i.e., optimal no matter what the defense strategy is) and universal (i.e., independent of the underlying sources) and we derive equilibrium strategies for both parties
Competitive Minimax Universal Decoding for Several Ensembles of Random Codes ∗
No full textUniversally achievable error exponents pertaining to certain families of channels (most notably, discrete memoryless channels (DMC’s)), and various ensembles of ran-dom codes, are studied by combining the competitive minimax approach, proposed by Feder and Merhav, with Chernoff bound and Gallager’s techniques for the analysis of error exponents. In particular, we derive a single–letter expression for the largest, uni-versally achievable fraction ξ of the optimum error exponent pertaining to the optimum ML decoding. Moreover, a simpler single–letter expression for a lower bound to ξ is presented. To demonstrate the tightness of this lower bound, we use it to show that ξ = 1, for the binary symmetric channel (BSC), when the random coding distribution is uniform over: (i) all codes (of a given rate), and (ii) all linear codes, in agreement with well–known results. We also show that ξ = 1 for the uniform ensemble of system-atic linear codes, and for that of time–varying convolutional codes in the bit-error–rate sense. For the latter case, we also show how the corresponding universal decoder can be efficiently implemented using a slightly modified version of the Viterbi algorithm which employs two trellises. Index Terms: error exponent, universal decoding, generalized likelihood ratio test, channel uncertainty, competitive minimax, Viterbi algorithm, maximum mutual infor-mation decoding
Universal decoding for arbitrary channels relative to a given class of decoding metrics
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