Optimum symbol-by-symbol mean-square error channel coding

An(n,k)linear block code is used to conveykinformation digits, each having a numerical value attached, in such a way as to minimize the mean-square error of the individual information digits regardless of the other(k-1)positions. This criterion is used because it provides a graceful degradation in the coding performance when the channel temporarily becomes less reliable. Unambiguous encoding is employed, and the channel is assumed to obey a realistic additive property. An optimum pair of symbol encoding and decoding functions are derived, and it is shown that the optimum symbol encoding can be performed in a linear fashion. The related decoding role is the conditional mean estimator. Fourier transforms are central to the optimal design of both rules. The optimum symbol rules tire identical with the properly isolated parts of the optimum mean-square error rules when the code is used to carry the k Information digits considered as a single complete numerical entity, The same channel coding design is therefore optimum for a wide variety of Information configurations. Techniques for implementing the optimum symbol decoders are examined with special emphasis on memoryless channels where the storage requirements for the necessary weighting coefficients are drastically reduced.     

七位量子信道编码与纠错

在量子网络的两个站点间通信时,一旦数据帧中出现误码就需要重新发送数据帧,此举虽然能够保证数据的正确性,但是在一定程度上增加了信道的压力、降低了通信效率。为了缓解信道压力,从量子态的复制、隐形传送的过程出发,针对现有的量子纠错电路进行分析和改进,设计出了七粒子纠缠态的量子纠错线路,七粒子纠缠态量子纠错可以纠正不多于3位量子态出现的位反转或者位相翻转错误。并对改进前后协议的效率、信道的利用率进行对比,发现改进后的纠错电路能有效提高数据传输的效率,为以后多粒子纠错提供可参考的依据。     

On the design of mean-square error channel coding systems using cyclic codes

Channel coding systems that employ linear block codes can be designed according to a mean-square error criterion. The optimum encoder and decoder pair is determined by selecting special elements in a generalized frequency domain based upon the values of key parameters called ratio weights. Systems may be designed that employ either hard or soft decision variables in the decoder. When cyclic codes are used, a minimal ideal decomposition of the code space shows that the ratio weights possess constant values on certain subsets in the frequency domain. This permits a drastic reduction in the number of ratio weights that need to be computed. For a cyclic code withtminimal ideals, this design procedure narrows the search for constancy subsets of the ratio weights to(2^{t}-1)subsets of the general space. Only one ratio weight needs to be computed for each constancy subset.     

Alternate motion-compensated prediction for error resilient video coding

Since the quality of compressed video is vulnerable to errors, video transmission over unreliable Internet is very challenging today. Two-Hypothesis Motion-Compensated Prediction (THMCP) has been shown to have Error Resilience (ER) capability for video transmission, where each macroblock is predicted from its previous two frames. In this paper, we propose a novel ER approach named Alternate Motion-Compensated Prediction (AMCP). In addition to two-hypothesis prediction, one-hypothesis prediction is alternately used. We use some schemes to determine which kind of prediction should be used, so that in some cases of loss, the propagated error can be first decreased to some extent before it spreads to the subsequent frames. As a result, the expected converged error is less than that obtained from THMCP with fixed weights (THMCPF). Both analysis and simulation results are given to show that AMCP performs better than THMCPF, in terms of both compression efficiency and ER capability.     

Novel prediction schemes for error resilient video coding

A conventional video codec uses encoder reconstruction of previous frames for motion compensated prediction. This is designed to minimize the encoder prediction error and assumes error free transmission. In this paper we use a modified prediction mechanism both at the encoder and decoder and propose techniques to improve the error resilience of H.264/AVC when transmitted over error prone networks. In our schemes we provide greater emphasis on Intra pixels during the formation of the reference frame used for prediction, thereby achieving better resilience. We also incorporate leaky prediction to further improve the robustness. We apply leaky prediction selectively at a macroblock level based on a simple mean square error metric in order to reduce the bit-rate penalty. Substantial performance gains have been observed in simulations. The effectiveness of using leaky prediction can be observed in medium and fast moving video sequences.     

基于LMS的图像自适应预测编码

为了提高图像编码预测器的预测性能,提出了一种低复杂度,高效的自适应预测方法。采用LMS(Least MeanSquare)自适应滤波技术进行预测,并对预测值进行减邻域均值的改进,有效克服了图像的非零均值和非平稳性特征,满足LMS算法的要求,使预测性能得以提高。通过对不同图像的仿真结果表明,该方法的预测差值图像的熵比GAP算法和MED算法的差值图像的熵要小0.1 bit/piexl左右,均方误差(MSE)也要小于后两者的均方误差。     

Adaptive blind channel equalisation in chaotic communications by using nonlinear prediction technique

In chaotic communications, an ideal channel is often assumed. In practice, channel distortion is inevitable. In particular, in wireless chaotic communications, the channel distortion may be serious and must be compensated. An adaptive blind equalisation algorithm is proposed. The aim of the algorithm is to recover the chaotic signal transmitted through a finite impulse response (FIR) channel. The inherent characteristic of the chaotic signal, that is the high sensitivity to initial conditions, is exploited to formulate the criterion used in deriving the algorithm. The analysis of stability of the proposed algorithm is also provided     

Adaptive channel error protection of subband encoded images

Protection of images that are encoded using subband coding from channel error is addressed. In this scheme the low-pass subband is encoded using DPCM (differential pulse-code modulation), and the other subbands are encoded using a scalar quantizer. The quantizers are all Lloyd-Max quantizers, from which the representation levels have fixed length codewords. First, considering only single errors in each codeword, a channel error distortion measure is derived for each quantizer, that is, for each subband. Codewords are assigned to the quantizer representation levels, yielding a low value of the distortion measure. Next, sets S_ij consisting of the jth bit from subband i are formed. Each set S _ij is assigned a particular BCH code C_ij. An algorithm that optimally assigns BCH codes C_ij to each set S_ij, based on a channel error distortion measure for the entire image, is derived. The protection scheme is adaptive, because each set of bits within each subband can be assigned a different error protection code. Examples show that this approach is preferable to assigning equal error protection codes to each set of bits. It is shown that in the case of a channel error probability of 10 ^-3, only 5% to 10% extra bits are needed for adequate channel error protection     

Adaptive image coding using spectral classification

We present a new classification scheme, dubbed spectral classification, which uses the spectral characteristics of the image blocks to classify them into one of a finite number of classes. A vector quantizer with an appropriate distortion measure is designed to perform the classification operation. The application of the proposed spectral classification scheme is then demonstrated in the context of adaptive image coding. It is shown that the spectral classifier outperforms gain-based classifiers while requiring a lower computational complexity.     

Autoregression estimation using final prediction error

We propose a modification of the autoregressive estimation based on residual emergy ratios that employs the Final Prediction Error (FPE) quantity of Akaike. The effect is to "taper" the partial correlation coefficient estimates by a multiplicative factor depending on model order and the number of observations.     

Random coding error exponents for flat fading channels withrealistic channel estimation

There has been a considerable interest in determining the limits to communications over multipath fading channels. However, most studies have assumed that the channel is perfectly known at the receiver. In this paper, the random coding error exponent for flat fading channels with realistic channel state information (CSI) is studied. It is assumed that the CSI is obtained via some practical technique which utilizes a linear estimation scheme. Two commonly used techniques for channel estimation are considered in this paper, namely pilot tone extraction and pilot symbol transmission. The degradation in the achievable performance due to partial CSI is assessed and comparison of the different channel estimation methods is made. The focus of this paper is on the Jake's mobile Rayleigh flat fading model. Although Jake's model does not have a Markov property, such as that found in the commonly used exponential correlation model, which is usually attractive from the mathematical tractability point of view, Jake's model has a physical basis. Also, this model is considered herein from the standpoint of the random coding exponent. The results in this paper shed light on the amount of degradation in the achievable performance that is expected when the receiver has partial CSI. Finally, the sensitivity of the loss in achievable performance for the various channel estimation techniques with respect to channel parameters, such as Doppler spread and signal-to-noise ratio (SNR), is studied     

Improved block truncation coding using modified error diffusion

Block truncation coding (BTC) is an efficient compression technique, offering good image quality. Nonetheless, the blocking effect inherent in BTC causes severe perceptual artefact when compression ratio is increased. Conversely, error diffusion (EDF) enjoys the benefit of diffusing the quantised error into neighbouring pixels. Consequently, the average tones in any local areas of the error-diffused image are preserved unchanged. Presented is a hybrid approach which combines the proposed modified EDF with BTC. As documented in experimental results, image quality is much better than BTC, and the complexity is even lower than traditional BTC.     

H.264 error resilience coding based on multi-hypothesis motion-compensated prediction

In this paper, we propose efficient schemes for enhancing the error robustness of multi-hypothesis motion-compensate predictive (MHMCP) coder without sacrificing the coding efficiency significantly. The proposed schemes utilize the concept of reference picture interleaving and data partitioning to make the MHMCP-coded video more resilient to channel errors, especially for burst channel error. Besides, we also propose a scheme of integrating adaptive intra-refresh into the proposed MHMCP coder to further improve the error recovery speed. Extensive simulation results show that the proposed methods can effectively and quickly mitigate the error propagation and the penalty on coding efficiency for clean channels due to the inserted error resilience features is rather minor.     

Flash scene video coding using weighted prediction

A novel algorithm for coding flash scenes is proposed. In principle, flash scenes can be detected by analyzing the histogram differences between frames. The proposed algorithm then suggests an adaptive coding order technique for increasing the efficiency of video coding by taking account of characteristics of flash scenes in video contents. The use of adaptive coding technique also benefits to enhance the accuracy of derived motion vectors for determination of weighting parameter sets. Experimental results show that a significant improvement of coding performance in terms of bitrate and PSNR can be achieved in comparison with the conventional weighted prediction algorithms.     

基于纠错算术码的信源信道自适应联合编解码系统

对信源信道自适应联合编码方法进行了研究,提出了一种新的基于纠错算术码的联合信源信道编解码系统。该系统在编码端利用算术码内嵌禁用符号实现信源信道一体式编码,即利用马尔科夫信源模型和根据信道状态信息自适应地调整禁用符号概率大小从而调整编码码率来实现信道自适应;在解码端,推导出了基于MAP的解码测度数学公式并基于此测度公式提出了一种改进的堆栈序列估计算法。与传统的信道自适应编码算法不同,该自适应编码算法只需调整一个参数:禁用符号,且理论上可获得连续可变的编码码率。实验结果表明,与经典的Grangetto联合编码系统以及分离编码系统相比,所提出的编码系统具有明显改善的性能增益。     

Non-redundant VQ channel coding using tabu search strategy

The tabu search approach is applied to codevector index assignment for noisy channels for the purpose of minimising the distortion due to bit errors without introducing any redundancy. Experimental results demonstrate the robustness of this approach compared with the standard parallel genetic algorithm and the binary switching algorithm     

Joint source/channel coding using arithmetic codes

Reserving space fur a symbol that is not in the source alphabet has been shown to provide excellent error detection. In this paper, we show how to exploit this capability using two sequential decoder structures to provide powerful error correction capability. This joint source/channel coder design provides significant packet loss recovery with minimal rate overhead, and compares favorably with conventional schemes     

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     

基于联想记忆的彩色图像自适应预测编码方法

本文利用牛顿前向插值多项式构建一种联想记忆型神经网络,并基于联想记忆提出一种彩色图像的自适应预测无损编码方法。针对彩色图像帧间相关性较大的特点,首先用R,G,B-G替代R,G,B以减小帧间相关性,然后对R 单独进行预测编码,对C,B—G进行二维矢量预测编码进一步减小空间相关和帧间相关,最后对预测残差进行算术编码。实验证明该算法是可行性的和有效性的,对测试图像的压缩效果优于JPEG-LS标准。