Progressive transmission of images using MAP detection overchannels with memory

We propose a new maximum a posteriori (MAP) detector, without the need for explicit channel coding, to lessen the impact of communication channel errors on compressed image sources. The MAP detector exploits the spatial correlation in the compressed bitstream as well as the temporal memory in the channel to correct channel errors. We first present a technique for computing the residual redundancy inherent in a compressed grayscale image (compressed using VQ). The performance of the proposed MAP detector is compared to that of a memoryless MAP detector. We also investigate the dependence of the performance on memory characteristics of the Gilbert-Elliott channel as well as average channel error rate. Finally, we study the robustness of the proposed MAP detector's performance to estimation errors.     

噪声信道中基于残留冗余的联合信源信道编码.

对信源编码中的残留冗余在联合编码中的作用进行了研究，提出了一个在噪声信道中对可变长信源编码码流传输提供有效差错保护的联合信源信道编码方法，该方法利用信源编码器输出中的残留冗余为传输码流提供差错保护。与Sayood K提出的系统相比，该方法是基于改进的联合卷积软解码以及采用非霍夫曼码的通用可变长码，更接近于一般的信源和信道编码方法，并且信源符号集的大小也不受限制。仿真表明，所提出的联合编码方法可获得比传统的分离编码方法更高的性能增益。     

噪声信道中基于残留冗余的联合信源信道编码

对信源编码中的残留冗余在联合编码中的作用进行了研究,提出了一个在噪声信道中对可变长信源编码码流传输提供有效差错保护的联合信源信道编码方法,该方法利用信源编码器输出中的残留冗余为传输码流提供差错保护。与SayoodK提出的系统相比,该方法是基于改进的联合卷积软解码以及采用非霍夫曼码的通用可变长码,更接近于一般的信源和信道编码方法,并且信源符号集的大小也不受限制。仿真表明,所提出的联合编码方法可获得比传统的分离编码方法更高的性能增益。     

Detection of binary Markov sources over channels with additiveMarkov noise

We consider maximum a posteriori (MAP) detection of a binary asymmetric Markov source transmitted over a binary Markov channel. The MAP detector observes a long (but finite) sequence of channel outputs and determines the most probable source sequence. In some cases, the MAP detector can be implemented by simple rules such as the “believe what you see” rule or the “guess zero (or one) regardless of what you see” rule. We provide necessary and sufficient conditions under which this is true. When these conditions are satisfied, the exact bit error probability of the sequence MAP detector can be determined. We examine in detail two special cases of the above source: (i) binary independent and identically distributed (i.i.d.) source and (ii) binary symmetric Markov source. In case (i), our simulations show that the performance of the MAP detector improves as the channel noise becomes more correlated. Furthermore, a comparison of the proposed system with a (substantially more complex) traditional tandem source-channel coding scheme portrays superior performance for the proposed scheme at relatively high channel bit error rates. In case (ii), analytical as well as simulation results show the existence of a “mismatch” between the source and the channel (the performance degrades as the channel noise becomes more correlated). This mismatch is reduced by the use of a simple rate-one convolutional encoder     

Optimal detection of discrete Markov sources over discretememoryless channels-applications to combined source-channel coding

The authors consider the problem of detecting a discrete Markov source which is transmitted across a discrete memoryless channel. Two maximum a posteriori (MAP) formulations are considered: (i) a sequence MAP detection in which the objective is to determine the most probable transmitted sequence given the observed sequence and (ii) an instantaneous MAP detection which is to determine the most probable transmitted symbol at time n given all the observations prior to and including time n. The solution to the first problem results in a “Viterbi-like” implementation of the MAP detector (with Large delay) while the latter problem results in a recursive implementation (with no delay). For the special case of the binary symmetric Markov source and binary symmetric channel, simulation results are presented and an analysis of these two systems yields explicit critical channel bit error rates above which the MAP detectors become useful. Applications of the MAP detection problem in a combined source-channel coding system are considered. Here, it is assumed that the source is highly correlated and that the source encoder (a vector quantizer (VQ)) fails to remove all of the source redundancy. The remaining redundancy at the output of the source encoder is referred to as the “residual” redundancy. It is shown, through simulation, that the residual redundancy can be used by the MAP detectors to combat channel errors. For small block sizes, the proposed system beats Farvardin and Vaishampayan's channel-optimized VQ by wide margins. Finally, it is shown that the instantaneous MAP detector can be combined with the VQ decoder to form an approximate minimum mean-squared error decoder     

Arithmetic coding-based continuous error detection for efficientARQ-based image transmission

Block cyclic redundancy check (CRC) codes are typically used to perform error detection in automatic repeat request (ARQ) protocols for data communications. Although efficient, CRCs can detect errors only after an entire block of data has been received and processed. We propose a new “continuous” error detection scheme using arithmetic coding that provides a novel tradeoff between the amount of added redundancy and the amount of time needed to detect an error once it occurs. This method of error detection, first introduced by Bell, Witten, and Cleary (1990), is achieved through the use of an arithmetic codec, and has the attractive feature that it can be combined physically with arithmetic source coding, which is widely used in state of-the-art image coders. We analytically optimize the tradeoff between added redundancy and error-detection time, achieving significant gains in bit rate throughput over conventional ARQ schemes for binary symmetric channel models for all probabilities of error     

Codebook organization to enhance maximum a posteriori detection ofprogressive transmission of vector quantized images over noisy channels

We describe a new way to organize a full-search vector quantization codebook so that images encoded with it can be sent progressively and have resilience to channel noise. The codebook organization guarantees that the most significant bits (MSBs) of the codeword index are most important to the overall image quality and are highly correlated. Simulations show that the effective channel error rates of the MSBs can be substantially lowered by implementing a maximum a posteriori (MAP) detector similar to one suggested by Phamdo and Farvardin (see IEEE Trans. Inform. Theory, vol.40, no.1, p.156-193, 1994). The performance of the scheme is close to that of pseudo-gray coding at lower bit error rates and outperforms it at higher error rates. No extra bits are used for channel error correction.     

Progressive transmission of images over fading channels using rate-compatible LDPC codes.

In this paper, we propose a combined source/channel coding scheme for transmission of images over fading channels. The proposed scheme employs rate-compatible low-density parity-check codes along with embedded image coders such as JPEG2000 and set partitioning in hierarchical trees (SPIHT). The assignment of channel coding rates to source packets is performed by a fast trellis-based algorithm. We examine the performance of the proposed scheme over correlated and uncorrelated Rayleigh flat-fading channels with and without side information. Simulation results for the expected peak signal-to-noise ratio of reconstructed images, which are within 1 dB of the capacity upper bound over a wide range of channel signal-to-noise ratios, show considerable improvement compared to existing results under similar conditions. We also study the sensitivity of the proposed scheme in the presence of channel estimation error at the transmitter and demonstrate that under most conditions our scheme is more robust compared to existing schemes.     

一种适用于丢包信道的小波编码图像传输方案

该文提出一种适用于丢包信道的基于小波变换的可伸缩图像编码传输方案。该方案利用分层多描述编码来提高信源编码的容错性能,利用信道编码来提高系统整体的抗丢包性能,采用编码后率失真优化技术对信源编码进行优化。利用非系统的RS码对信源编码符号和信道编码符号进行重新排序,将分层多描述编码和信道编码进行了有效的结合。通过在编解码端采用相同的排序算法,来减少传输开销。仿真结果表明,该方案与现有的方案相比,提高了接收图像的质量,并且需要较少的传输开销。     

Content-based multiple bitstream image transmission over noisy channels

We propose a novel combined source and channel coding scheme for image transmission over noisy channels. The main feature of the proposed scheme is a systematic decomposition of image sources so that unequal error protection can be applied according to not only bit error sensitivity but also visual content importance. The wavelet transform is adopted to hierarchically decompose the image. The association between the wavelet coefficients and what they represent spatially in the original image is fully exploited so that wavelet blocks are classified based on their corresponding image content. The classification produces wavelet blocks in each class with similar content and statistics, therefore enables high performance source compression using the set partitioning in hierarchical trees (SPIHT) algorithm. To combat the channel noise, an unequal error protection strategy with rate-compatible punctured convolutional/cyclic redundancy check (RCPC/CRC) codes is implemented based on the bit contribution to both peak signal-to-noise ratio (PSNR) and visual quality. At the receiving end, a postprocessing method making use of the SPIHT decoding structure and the classification map is developed to restore the degradation due to the residual error after channel decoding. Experimental results show that the proposed scheme is indeed able to provide protection both for the bits that are more sensitive to errors and for the more important visual content under a noisy transmission environment. In particular, the reconstructed images illustrate consistently better visual quality than using the single-bitstream-based schemes.     

Space-time coding ambiguities in joint adaptive channel estimation and detection

This paper studies the error propagation effect that is caused by certain ambiguities in joint data detection-channel tracking algorithms for transmission diversity schemes. Here, we use a space-time (ST) receiver based on the maximum a posteriori (MAP) method that takes into account the channel estimation error assuming the unknown channel to have a given complex multivariate Gaussian probability density function (pdf) (i.e., a Ricean channel). The decision criterion that is expressed in quadratic form represents either a linear detector or a noncoherent-nonlinear detector in extreme cases. Then, the channel pdf for the next iteration is updated by estimates of the second-order statistics of the channel coefficients, and a very simple decision-directed adaptive algorithm is derived for adaptive channel estimation. The adaptive algorithm can efficiently track a fast Rayleigh fading channel and, as a result, achieves robust performance. However, the occurrence of two types of ambiguities initiated in deep fades result in error propagation. Some remedies called space-time ambiguity remedies (STARs) are proposed to prevent error propagation. A new time-varying space-time coding (TVST) scheme is suggested as a bandwidth-efficient method to combat the permutation ambiguity impairment. This coding scheme, in conjunction with a differential detector, can resolve the ambiguity problem.     

快速Internet小波图像传输

图像通常利用无损协议（如ＴＣＰ／ＩＰ）在因特网上进行传输。无损协议需要重发丢失的数据包,而这必然引起传输时间的增加。本文介绍了压缩图像的一种快速有损因特网图像传输方案（ＦＬＩＩＴ）。它通过添加冗余比特保护图像的重要部分来消除重发时延。文中论述了一种高效地分配量化比特和冗余比特来控制量误差和预测数据包传输丢失的信源和信道联合编码算法。并讨论了这种算法的实现过程,以及将它在Ｉｎｔｅｒｎｅｔ上传输的性能     

Dual link distributed source coding scheme for the transmission of satellite hyperspectral imagery

Traditional lossless compression methods for satellite hyperspectral imagery focus on exploiting spatial and/or spectral redundancy. Those methods do not consider the temporal redundancy between images of the same area that are captured at different times. To exploit the temporal redundancy between hyperspectral images and reduce the amount of information to be transmitted from the space-satellite to the ground station via the downlink, this paper introduces a dual link distributed source coding (DLDSC) scheme for hyperspectral space-satellite communication. The proposed scheme employs the space-satellite dual link (i.e., the downlink and the uplink). The satellite onboard uses some side information from the ground station to calculate the hyperspectral image band coset values, and then, without syndrome coding, transmits to the ground station via the downlink. Coset coding is a typical technique used in distributed source coding (DSC), and here the coset values represent the timely hyperspectral image details. Typically, the coset values have lower entropy than that of the original source values. To exploit the temporal redundancy, the side information is computed in the ground station using the image captured at the previous time for the same area and transmitted to the space-satellite via the uplink. Hyperspectral images from the Hyperion satellite are used for the validation of the proposed scheme. The experimental results indicate that the proposed DLDSC scheme can reduce the original signal entropy by approximately 3.2 bits per sample (bps) and can achieve up to 1.0 bps and 1.6 bps gains over the lossless JPEG2000 standard and the state-of-art predictive CCSDS-123 method, respectively.     

Joint source-channel coding using real BCH codes for robust image transmission.

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 Bernoulli-Gaussian 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 state-of-art 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 well tuned for a given channel situation, the joint coding scheme shows an increased robustness as the channel conditions worsen. The soft performance degradation observed when the channel worsens gives an additional advantage to the joint source-channel coding scheme for fading channels, since a reconstruction with moderate quality may be still possible, even if the channel is in a deep fade.     

Operational rate-distortion performance for joint source andchannel coding of images

This paper describes a methodology for evaluating the operational rate-distortion behavior of combined source and channel coding schemes with particular application to images. In particular, we demonstrate use of the operational rate-distortion function to obtain the optimum tradeoff between source coding accuracy and channel error protection under the constraint of a fixed transmission bandwidth for the investigated transmission schemes. Furthermore, we develop information-theoretic bounds on performance for specific source and channel coding systems and demonstrate that our combined source-channel coding methodology applied to different schemes results in operational rate-distortion performance which closely approach these theoretical limits. We concentrate specifically on a wavelet-based subband source coding scheme and the use of binary rate-compatible punctured convolutional (RCPC) codes for transmission over the additive white Gaussian noise (AWGN) channel. Explicit results for real-world images demonstrate the efficacy of this approach.     

Use of residual redundancy in the design of joint source/channelcoders

A technique for providing error protection without the additional overhead required for channel coding is presented. The authors start from the premise that, during source coder design, for the sake of simplicity or due to imperfect knowledge, assumptions have to be made about the source which are often incorrect. This results in residual redundancy at the output of the source coder. The residual redundancy can then be used to provide error protection in much the same way as the insertion of redundancy in convolutional coding provides error protection. The authors develop an approach for utilizing this redundancy. To show the validity of this approach, the authors apply it to image coding using differential pulse code modulation (DPCM), and obtain substantial performance gains, both in terms of objective and subjective measures     

Recent Results on the Use of Concatenated Reed-Solomon/Viterbi Channel Coding and Data Compression for Space Communications

The development of sophisticated adaptive source coding algorithms together with inherent error sensitivity problems fostered the need for efficient space communication at very low bit error probilbilities(leq 10^{-6}). This led to the specification and implementation of a concatenated coding system using an interleaved Reed-Solomon code as the outer code and a Viterbi-decoded convolutionai code as the inner code. This paper presents the experimental results of this channel coding system under an emulatedS-band uplink andX-band downlink two-way space communication channel, where both uplink and downlink have strong carrier power. Test results verify that at a bit error probability of 10^-6or less, this concatenated coding system does provide a coding gain of 2.5 dB or more over the viterbi-decoded convolutional-only coding system. These tests also show that a desirable interleaving depth for the Reed-Solomon outer code is 8 or more. The imptict of this "virtually" error-free space communication link on the transmission of images is discussed and examples of Simulation results are given.     

Sequence MAP decoding of trellis codes for Gaussian and Rayleighchannels

This paper considers the use of sequence maximum a posteriori (MAP) decoding of trellis codes. A MAP receiver can exploit any “residual redundancy” that may exist in the channel encoded signal in the form of memory and/or a nonuniform distribution, thereby providing enhanced performance over very noisy channels, relative to maximum likelihood (ML) decoding. The paper begins with a first-order two-state Markov model for the channel encoder input. A variety of different systems with different source parameters, different modulation schemes, and different encoder complexities are simulated. Sequence MAP decoding is shown to substantially improve performance under very noisy channel conditions for systems with low-to-moderate redundancy, with relative gain increasing as the rate increases. As a result, coding schemes with multidimensional constellations are shown to have higher MAP gains than comparable schemes with two-dimensional (2-D) constellations. The second part of the paper considers trellis encoding of the code-excited linear predictive (CELP) speech coder's line spectral parameters (LSPs) with four-dimensional (4-D) QPSK modulation. Two source LSP models are used. One assumes only intraframe correlation of LSPs while the second one models both intraframe and interframe correlation. MAP decoding gains (over ML decoding) as much as 4 dB are achieved. Also, a comparison between the conventionally designed codes and an I-Q QPSK scheme shows that the I-Q scheme achieves better performance even though the first (sampler) LSP model is used     

Joint lossless-source and channel coding using automatic repeatrequest

The susceptibility of arithmetic coding to errors is utilized for channel error recovery using an automatic repeat request (ARQ) scheme. The presented scheme optimizes the tradeoff between the redundancy added to overcome channel errors and detection capability. With this approach, the type of error pattern introduced by the channel does not affect the receiver's detection capability. This scheme is suitable for transmitting long files over low bit error rate channels, and it provides the assurance of reconstructing the original data, free from catastrophic errors     

Progressive image transmission over differentially space‐time coded OFDM systems

In this paper, we consider progressive image transmission over differentially space‐time coded orthogonal frequency‐division multiplexing (OFDM) systems and treat the problem as one of optimal joint source‐channel coding (JSCC) in the form of unequal error protection (UEP), as necessitated by embedded source coding (e.g., SPIHT and JPEG 2000). We adopt a product channel code structure that is proven to provide powerful error protection and employ low‐complexity decision‐feedback decoding for differentially space‐time coded OFDM without assuming channel state information. For a given SNR, the BER performance of the differentially space‐time coded OFDM system is treated as the channel condition in the JSCC/UEP design via a fast product code optimization algorithm so that the end‐to‐end quality of reconstructed images is optimized in the average minimum MSE sense. Extensive image transmission experiments show that SNR/BER improvements can be translated into quality gains in reconstructed images. Moreover, compared to another non‐coherent detection algorithm, i.e., the iterative receiver based on expectation‐maximization algorithm for the space‐time coded OFDM systems, differentially space‐time coded OFDM systems suffer some quality loss in reconstructed images. With the efficiency and simplicity of decision‐feedback differential decoding, differentially space‐time coded OFDM is thus a feasible modulation scheme for applications such as wireless image over mobile devices (e.g., cell phones). Copyright © 2006 John Wiley & Sons, Ltd.