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98
Quantization
 IEEE TRANS. INFORM. THEORY
, 1998
"... The history of the theory and practice of quantization dates to 1948, although similar ideas had appeared in the literature as long ago as 1898. The fundamental role of quantization in modulation and analogtodigital conversion was first recognized during the early development of pulsecode modula ..."
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Cited by 700 (12 self)
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The history of the theory and practice of quantization dates to 1948, although similar ideas had appeared in the literature as long ago as 1898. The fundamental role of quantization in modulation and analogtodigital conversion was first recognized during the early development of pulsecode modulation systems, especially in the 1948 paper of Oliver, Pierce, and Shannon. Also in 1948, Bennett published the first highresolution analysis of quantization and an exact analysis of quantization noise for Gaussian processes, and Shannon published the beginnings of rate distortion theory, which would provide a theory for quantization as analogtodigital conversion and as data compression. Beginning with these three papers of fifty years ago, we trace the history of quantization from its origins through this decade, and we survey the fundamentals of the theory and many of the popular and promising techniques for quantization.
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.
On the construction of some capacityapproaching coding schemes
, 2000
"... This thesis proposes two constructive methods of approaching the Shannon limit very closely. Interestingly, these two methods operate in opposite regions, one has a block length of one and the other has a block length approaching infinity. The first approach is based on novel memoryless joint source ..."
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Cited by 63 (2 self)
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This thesis proposes two constructive methods of approaching the Shannon limit very closely. Interestingly, these two methods operate in opposite regions, one has a block length of one and the other has a block length approaching infinity. The first approach is based on novel memoryless joint sourcechannel coding schemes. We first show some examples of sources and channels where no coding is optimal for all values of the signaltonoise ratio (SNR). When the source bandwidth is greater than the channel bandwidth, joint coding schemes based on spacefilling curves and other families of curves are proposed. For uniform sources and modulo channels, our coding scheme based on spacefilling curves operates within 1.1 dB of Shannon’s ratedistortion bound. For Gaussian sources and additive white Gaussian noise (AWGN) channels, we can achieve within 0.9 dB of the ratedistortion bound. The second scheme is based on lowdensity paritycheck (LDPC) codes. We first demonstrate that we can translate threshold values of an LDPC code between channels accurately using a simple mapping. We develop some models for density evolution
Robust Image Transmission over EnergyConstrained TimeVarying Channels Using Multiresolution Joint SourceChannel Coding
 IEEE TRANS. SIGNAL PROCESSING
, 1998
"... We explore joint sourcechannel coding (JSCC) for timevarying channels using a multiresolution framework for both source coding and transmission via novel multiresolution modulation constellations. We consider the problem of still image transmission over timevarying channels with the channel state ..."
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Cited by 27 (3 self)
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We explore joint sourcechannel coding (JSCC) for timevarying channels using a multiresolution framework for both source coding and transmission via novel multiresolution modulation constellations. We consider the problem of still image transmission over timevarying channels with the channel state information (CSI) available at 1) receiver only and 2) both transmitter and receiver being informed about the state of the channel, and we quantify the effect of CSI availability on the performance. Our source model is based on the wavelet image decomposition, which generates a collection of subbands modeled by the family of generalized Gaussian distributions. We describe an algorithm that jointly optimizes the design of the multiresolution source codebook, the multiresolution constellation, and the decoding strategy of optimally matching the source resolution and signal constellation resolution “trees” in
Quantization of memoryless and Gauss–Markov sources over binary Markov channels,” Univ
, 1994
"... Abstract — Joint source–channel coding for stationary memoryless and Gauss–Markov sources and binary Markov channels is considered. The channel is an additivenoise channel where the noise process is an Mthorder Markov chain. Two joint sourcechannel coding schemes are considered. The first is a ch ..."
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Cited by 27 (12 self)
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Abstract — Joint source–channel coding for stationary memoryless and Gauss–Markov sources and binary Markov channels is considered. The channel is an additivenoise channel where the noise process is an Mthorder Markov chain. Two joint sourcechannel coding schemes are considered. The first is a channeloptimized vector quantizer—optimized for both source and channel. The second scheme consists of a scalar quantizer and a maximum a posteriori detector. In this scheme, it is assumed that the scalar quantizer output has residual redundancy that can be exploited by the maximum a posteriori detector to combat the correlated channel noise. These two schemes are then compared against two schemes which use channel interleaving. Numerical results show that the proposed schemes outperform the interleaving schemes. For very noisy channels with high noise correlation, gains of 4–5 dB in signaltonoise ratio are possible. Index Terms — Channels with memory, joint source–channel coding, MAP detection, Markov noise, vector quantization. I.
Asymptotic Bounds on Optimal Noisy Channel Quantization Via Random Coding
, 1994
"... Asymptotically optimal zerodelay vector quantization in the presence of channel noise is studied using random coding techniques. First, an upper bound is derived for the average r th  power distortion of channel optimized kdimensional vector quantization at transmission rate R on a binary symm ..."
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Cited by 18 (3 self)
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Asymptotically optimal zerodelay vector quantization in the presence of channel noise is studied using random coding techniques. First, an upper bound is derived for the average r th  power distortion of channel optimized kdimensional vector quantization at transmission rate R on a binary symmetric channel with bit error probability ffl. The upper bound asymptotically equals 2 \GammarRg(ffl;k;r) , where k k+r h 1 \Gamma log 2 i 1 + 2 p ffl(1 \Gamma ffl) ji g(ffl; k; r) 1 for all ffl 0, lim ffl!0 g(ffl; k; r) = 1, and lim k!1 g(ffl; k; r) = 1. Numerical computations of g(ffl; k; r) are also given. This result is analogous to Zador's asymptotic distortion rate of 2 \GammarR for quantization on noiseless channels. Next, using a random coding argument on nonredundant index assignments, a useful upper bound is derived in terms of point density functions, on the minimum mean squared error of high resolution, regular, vector quantizers in the presence of channel noise. T...
Ratedistortion optimized hybrid error control for realtime packetized video transmission
 IEEE Trans. Image Processing
, 2004
"... Abstract — We study hybrid error control for realtime video transmission. The study is carried out using a proposed integrated joint sourcechannel coding framework, which jointly considers error resilient source coding, channel coding, and error concealment, in order to achieve the best video qual ..."
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Cited by 17 (4 self)
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Abstract — We study hybrid error control for realtime video transmission. The study is carried out using a proposed integrated joint sourcechannel coding framework, which jointly considers error resilient source coding, channel coding, and error concealment, in order to achieve the best video quality. We focus on the performance comparison of several error correction scenarios, such as forward error correction (FEC), retransmission, and the combination of both. Simulation results show that either FEC or retransmission can be optimal depending on the packet loss rates and network round trip time. The proposed hybrid FEC/retransmission scheme outperforms both. I.
Multiresolution Joint SourceChannel Coding for Wireless Channels
, 1998
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Combined Source/Channel (De)Coding: Can A Priori Information Be Used Twice?
 Proc. IEEE Int. Symp. Inform. Theory
, 2000
"... In digital transmission of speech, audio, images and video signals residual redundancy is often left after source coding due to the complexity and delay constraints. This redundancy remains both inside one block or frame but also in a time correlation of subsequent frames. We describe an approach to ..."
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Cited by 14 (1 self)
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In digital transmission of speech, audio, images and video signals residual redundancy is often left after source coding due to the complexity and delay constraints. This redundancy remains both inside one block or frame but also in a time correlation of subsequent frames. We describe an approach to improve channel and source decoding by using both kinds of correlation. Further on we consider the bitmapping and the multiplexing in coding and its effect on decoding. The mutual information as measurement for the gain in decoding through a priori information is explained. In this work on combined source and channel decoding, we try to answer the following question: Can a priori information that models the source parameters be used twice; first at the channel decoder and then at the source decoden The channel decoder uses the a priori informarion that models the bit stream generated by the source coden This doesn't capture all the details of the source parameter level statistics. By exploiting the a priori knowledge of parameters (once more) at the source decoder, we show that it is possible to achieve better reconstruction than if this information was used at either of the decoders.
Joint design of fixedrate source codes and multiresolution channel codes
 IEEE Trans. Commun
, 1998
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