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Error Control and Concealment for Video Communication  A Review
 PROCEEDINGS OF THE IEEE
, 1998
"... The problem of error control and concealment in video communication is becoming increasingly important because of the growing interest in video delivery over unreliable channels such as wireless networks and the Internet. This paper reviews the techniques that have been developed for error control a ..."
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Cited by 350 (11 self)
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The problem of error control and concealment in video communication is becoming increasingly important because of the growing interest in video delivery over unreliable channels such as wireless networks and the Internet. This paper reviews the techniques that have been developed for error control and concealment in the past ten to fifteen years. These techniques are described in three categories according to the roles that the encoder and decoder play in the underlying approaches. Forward error concealment includes methods that add redundancy at the source end to enhance error resilience of the coded bit streams. Error concealment by postprocessing refers to operations at the decoder to recover the damaged areas based on characteristics of image and video signals. Finally, interactive error concealment covers techniques that are dependent on a dialog between the source and destination. Both current research activities and practice in international standards are covered.
Deterministic Annealing for Clustering, Compression, Classification, Regression, and Related Optimization Problems
 Proceedings of the IEEE
, 1998
"... this paper. Let us place it within the neural network perspective, and particularly that of learning. The area of neural networks has greatly benefited from its unique position at the crossroads of several diverse scientific and engineering disciplines including statistics and probability theory, ph ..."
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Cited by 259 (11 self)
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this paper. Let us place it within the neural network perspective, and particularly that of learning. The area of neural networks has greatly benefited from its unique position at the crossroads of several diverse scientific and engineering disciplines including statistics and probability theory, physics, biology, control and signal processing, information theory, complexity theory, and psychology (see [45]). Neural networks have provided a fertile soil for the infusion (and occasionally confusion) of ideas, as well as a meeting ground for comparing viewpoints, sharing tools, and renovating approaches. It is within the illdefined boundaries of the field of neural networks that researchers in traditionally distant fields have come to the realization that they have been attacking fundamentally similar optimization problems.
Tradeoff Between Source and Channel Coding
 IEEE TRANS. INFORM. THEORY
, 1997
"... A fundamental problem in the transmission of analog information across a noisy discrete channel is the choice of channel code rate that optimally allocates the available transmission rate between lossy source coding and block channel coding. We establish tight bounds on the channel code rate that mi ..."
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Cited by 69 (5 self)
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A fundamental problem in the transmission of analog information across a noisy discrete channel is the choice of channel code rate that optimally allocates the available transmission rate between lossy source coding and block channel coding. We establish tight bounds on the channel code rate that minimizes the average distortion of a vector quantizer cascaded with a channel coder and a binarysymmetric channel. Analytic expressions are derived in two cases of interest: small biterror probability and arbitrary source vector dimension; arbitrary biterror probability and large source vector dimension. We demonstrate that the optimal channel code rate is often substantially smaller than the channel capacity, and obtain a noisychannel version of the Zador highresolution distortion formula.
Joint sourcechannel coding error exponent for discrete communication systems with Markovian memory
 IEEE Trans. Info. Theory
, 2007
"... Abstract—We investigate the computation of Csiszár’s bounds for the joint source–channel coding (JSCC) error exponent of a communication system consisting of a discrete memoryless source and a discrete memoryless channel. We provide equivalent expressions for these bounds and derive explicit formula ..."
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Cited by 24 (9 self)
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Abstract—We investigate the computation of Csiszár’s bounds for the joint source–channel coding (JSCC) error exponent of a communication system consisting of a discrete memoryless source and a discrete memoryless channel. We provide equivalent expressions for these bounds and derive explicit formulas for the rates where the bounds are attained. These equivalent representations can be readily computed for arbitrary source–channel pairs via Arimoto’s algorithm. When the channel’s distribution satisfies a symmetry property, the bounds admit closedform parametric expressions. We then use our results to provide a systematic comparison between the JSCC error exponent and the tandem coding error exponent, which applies if the source and channel are separately coded. It is shown that 2. We establish conditions for which and for which =2. Numerical examples indicate that is close to2 for many source– channel pairs. This gain translates into a power saving larger than 2 dB for a binary source transmitted over additive white Gaussian noise (AWGN) channels and Rayleighfading channels with finite output quantization. Finally, we study the computation of the lossy JSCC error exponent under the Hamming distortion measure. Index Terms—Discrete memoryless sources and channels, error exponent, Fenchel’s duality, Hamming distortion measure, joint source–channel coding, randomcoding exponent, reliability function, spherepacking exponent, symmetric channels, tandem source and channel coding. I.
Total System Energy Minimization for Wireless Image Transmission
 Journal of VLSI Signal Processing Systems
, 2001
"... In this paper, we focus on the totalsystemenergy mininfization of a wireless image transntission system including both digital and analog components. Traditionally, digital power consumption has been ignored in system design, since transnfit power has been the most significant component. Howeve ..."
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Cited by 17 (1 self)
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In this paper, we focus on the totalsystemenergy mininfization of a wireless image transntission system including both digital and analog components. Traditionally, digital power consumption has been ignored in system design, since transnfit power has been the most significant component. However, as we move to an era of picocell environments and as more complex signal processing algorithms are being used at higher data rates, the digital power consumption of these systems becomes an issue. We present an energyoptinfized image transnfission system for indoor wireless applications which exploits the variabilities in the image data and the wireless multipath channel by employing dynamic algorithm transformations and joint sourcechannel coding. The variability in the image data is characterized by the ratedistortion curve, and the variability in the channel characteristics is characterized by the pathloss and impulse response of the channel. The system hardware configuration space is characterized by the errorcorrection capability of the channel encoder/decoder, number of poweredup fingers in the RAKE receiver, and transmit power of the power amplifier. An optimization algorithm is utilized to obtain energyoptimal configurations subject to endtoend performance constraints. The proposed design is tested over QCIF images, IMT2000 channels and 0.18/m, 2.5V CMOS technology parameters. Simulation results over various images, various distances, two different channels, and two different rates show that the average energy savings in utilizing a totalsystemenergy mininfization over a fixed system (designed for the worst image, the worst channel and the maximum distance) are 53.6% and 67.3%, respectively, for shortrange (under 20m) and longrange (o...
Design and performance of VQbased hybrid digitalanalog joint sourcechannel codes
 IEEE Trans. Inform. Theory
, 2002
"... Abstract—A joint source–channel hybrid digital–analog (HDA) vector quantization (VQ) system is presented. The main advantage of the new VQbased HDA system is that it achieves excellent ratedistortioncapacity performance at the design signaltonoise ratio (SNR) while maintaining a “graceful impro ..."
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Cited by 14 (5 self)
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Abstract—A joint source–channel hybrid digital–analog (HDA) vector quantization (VQ) system is presented. The main advantage of the new VQbased HDA system is that it achieves excellent ratedistortioncapacity performance at the design signaltonoise ratio (SNR) while maintaining a “graceful improvement ” characteristic at higher SNRs. It is demonstrated that, within the HDA framework, the parameters of the system can be optimized using an iterative procedure similar to that of channeloptimized vector quantizer design. Comparisons are made with three purely digital systems and one purely analog system. It is found that, at high SNRs, the VQbased HDA system is superior to the other investigated systems. At low SNRs, the performance of the new scheme can be improved using the optimization procedure and using soft decoding in the digital part of the system. These results demonstrate that the introduced scheme provides an attractive method for terrestrial broadcasting applications. Index Terms—Broadcasting, hybrid digital–analog coding, joint source–channel coding, robust transmission, source coding, vector quantization (VQ). I.
Binary Lattice Vector Quantization with Linear Block Codes and Affine Index Assignments
, 1998
"... We determine analytic expressions for the performance of some lowcomplexity combined sourcechannel coding systems. The main tool used is the Hadamard transform. In particular, we obtain formulas for the average distortion of binary lattice vector quantization with affine index assignments, linear ..."
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Cited by 10 (3 self)
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We determine analytic expressions for the performance of some lowcomplexity combined sourcechannel coding systems. The main tool used is the Hadamard transform. In particular, we obtain formulas for the average distortion of binary lattice vector quantization with affine index assignments, linear block channel coding, and a binarysymmetric channel. The distortion formulas are specialized to nonredundant channel codes for a binarysymmetric channel, and then extended to affine index assignments on a binaryasymmetric channel. Various structured index assignments are compared. Our analytic formulas provide a computationally efficient method for determining the performance of various coding schemes. One interesting result shown is that for a uniform source and uniform quantizer, the Natural Binary Code is never optimal for a nonsymmetric channel, even though it is known to be optimal for a symmetric channel.
Joint SourceChannel Coding using Real BCH Codes for Robust Image Transmission
, 2006
"... In this paper, a new still image coding scheme is presented. In contrast with standard tandem coding schemes, where the redundancy is introduced after source coding, it is introduced before source coding using real BCH codes. A joint channel model is first presented. The model corresponds to a memor ..."
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Cited by 6 (4 self)
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In this paper, a new still image coding scheme is presented. In contrast with standard tandem coding schemes, where the redundancy is introduced after source coding, it is introduced before source coding using real BCH codes. A joint channel model is first presented. The model corresponds to a memoryless mixture of Gaussian and BernoulliGaussian noise. It may represent the source coder, the channel coder, the physical channel, and their corresponding decoder. Decoding algorithms are derived from this channel model and compared to a stateofart real BCH decoding scheme. A further comparison with two reference tandem coding schemes and the proposed joint coding scheme for the robust transmission of still images has been presented. When the tandem scheme is not accurately tuned, the joint coding scheme outperforms the tandem scheme in all situations. Compared to a tandem scheme welltuned for a given channel situation, the joint coding scheme shows an increased robustness as the channel conditions worsen.
Practical QuantizeandForward Schemes for the Frequency Division Relay Channel
, 2007
"... We consider relay channels in which the sourcedestination and relaydestination signals are assumed to be orthogonal and thus have to be recombined at the destination. Assuming memoryless signals at the destination and relay, we propose a lowcomplexity quantizeandforward (QF) relaying scheme, wh ..."
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Cited by 4 (4 self)
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We consider relay channels in which the sourcedestination and relaydestination signals are assumed to be orthogonal and thus have to be recombined at the destination. Assuming memoryless signals at the destination and relay, we propose a lowcomplexity quantizeandforward (QF) relaying scheme, which exploits the knowledge of the SNRs of the sourcerelay and relaydestination channels. Both in static and quasistatic channels, the quantization noise introduced by the relay is shown to be significant in certain scenarios. We therefore propose a maximum likelihood (ML) combiner at the destination, which is shown to compensate for these degradations and to provide significant performance gains. The proposed association, which comprises the QF protocol and ML detector, can be seen, in particular, as a solution for implementing a simple relaying protocol in a digital relay in contrast with the amplifyandforward protocol which is an analog solution.
Efficient source decoding over memoryless noisy channels using higherorder Markov models
 IEEE TRANS. INFORM. THEORY
, 2004
"... Exploiting the residual redundancy in a source coder output stream during the decoding process has been proven to be a bandwidthefficient way to combat noisy channel degradations. This redundancy can be employed to either assist the channel decoder for improved performance or design better source d ..."
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Cited by 4 (3 self)
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Exploiting the residual redundancy in a source coder output stream during the decoding process has been proven to be a bandwidthefficient way to combat noisy channel degradations. This redundancy can be employed to either assist the channel decoder for improved performance or design better source decoders. In this work, a family of solutions for the asymptotically optimum minimum meansquared error (MMSE) reconstruction of a source over memoryless noisy channels is presented when the redundancy in the source encoder output stream is exploited in the form of aorder Markov model @ IA and a delay of H is allowed in the decoding process. It is demonstrated that the proposed solutions provide a wealth of tradeoffs between computational complexity and the memory requirements. A simplified MMSE decoder which is optimized to minimize the computational complexity is also presented. Considering the same problem setup, several other maximum a posteriori probability (MAP) symbol and sequence decoders are presented as well. Numerical results are presented which demonstrate the efficiency of the proposed algorithms.