Configurable variable length code with genetic algorithms

H.264/AVC entropy decoder complexity analysis and its applications

Joint source-channel decoding of variable length codes (VLC) for image and video streaming transmission over unreliable links, such as wireless networks, is a subject of increasing interest. Much more residual source redundancy can be exploited when both types of correlation: (i) the correlation between bits inside a VLC codeword as well as; (ii) the correlation between VLC codewords of a VLC sequence unit (e.g. corresponding to one image block), are taken into account. The paper (Hang Nguyen et al, IEEE Int. Conf. on Acoustics, Speech, and Sigpro., 2004) proposes an optimum maximum likelihood (ML) decoder of VLC sequences which can exploit these two kinds of correlation and outperforms the existing VLC decoders. This paper proposes a reduced complexity version of this optimal VLC decoder. Simulation results show that the complexity is reduced by 5 in terms of number of possible candidates, while the performance is only slightly sub-optimal compared with the optimal version of the Hang Nguyen paper.

Variable length codes (VLC) have found widespread use for efficient encoding of symbols with unequal probabilities in many practical situations. However, bit errors can cause a loss of decoder synchronism that often leads to error propagation. Recent advances in the development of VLC that limit the effect of error propagation, such as reversible VLC and self-synchronising VLC, contribute further to their popularity. However, it is still important to model the performance of various VLC code sets so that comparisons can be made between different coding schemes and for different applications. Communicating sequential processes (CSP) is a well-established formal description technique that allows one to analyse the behaviour of concurrently evolving processes. It has been successfully applied to industrial-scale problems. The paper describes how CSP can be applied to the modelling of the resync process of VLC. This approach offers three main advantages. First, a complete model comprises processes and events as basic building blocks, making this approach highly scalable. Second, different semantic models provide different level of abstraction. Third, tools are available for automatic generation of sync sequences, which also provide a measure of sync performance. This facilitates comparisons of different VLC schemes in addition to code sets obtained using a given coding scheme.

In this paper, we describe a structured variable length coding (VLC) based on Golomb code that generalize the current context-based adaptive variable length coding (CAVLC) in the emerging video coding standard H.264/AVC. The current CAVLC is characterized as unstructured VLC and uses extensive dedicated code tables. Lack of generality due to these code tables causes a problem of over-fitting or over-learning when we estimate a set of coding parameters. We propose a compact structured code based on Golomb code providing generality, extensibility, and low implementation complexity with only three parameters. Introduction of a simple truncation method enables to avoid reversed order code length and remove unused code space for finite set of symbols. Experimental results show its similar coding efficiency to current CAVLC while reducing the size of memories to store code tables and providing adaptability for various probability functions.

Variable length codes (VLCs), used in data compression, are very sensitive to error propagation in the presence of noisy channels. To address this problem, several joint source channel turbo techniques have been proposed in the literature. In this paper, we focus on pairs of source/VLC of low redundancy, i.e., when there is a good match between the source statistics and the length distribution of the VLC. It is a case not considered extensively in the literature so far and the classical concatenation of a VLC and a convolutional code is not satisfying. Through EXIT chart and interleaving gain analysis, we show that the introduction of a repetition code between the VLC and the convolutional code considerably improves global performance. In particular, excellent symbol error rates are obtained with reversible VLCs which are used in recent source codecs.

A concurrent variable length coding (VLC) decoder, introduced in Hsieh and Kim (1996) and Shaw-Min Lei and Ming-Ting Sun (1989), can achieve high system performance by decoding VLC codes concurrently by exploiting the principle of variable-length coding statistical characteristics, shorter codewords appear often. For concurrent VLC decoding, the better the decoding throughput, the more complicated the hardware and control. Therefore, a compromise should be made between performance and cost. In this paper, a systematic approach based on mathematical models for a concurrent VLC decoder is proposed. The tradeoff between system performance and hardware cost is investigated.

The recent H.264 video coding standard adopted context-based adaptive variable length coding (CAVLC) as the entropy coding tool. By combining adaptive variable length coding (VLC) with context modeling, we can achieve a high degree of redundancy reduction. However, CAVLC in H.264 has a problem that correctness of VLC table prediction is low. In this paper, we propose a new VLC table prediction algorithm using both the correlation of coding mode and the statistics of mode distribution in both intra and inter frames. Experimental results show that the proposed algorithm reduces the bit rate by 0.94% on average.

An efficient architecture of variable length coding (VLC) is developed for recent multimedia applications, such as video and image compression. VLC plays a crucial part in these applications in that it provides a very effective coding gain. In this paper, we will describe an architecture design of VLC encoder. It can produce VLC codeword and amplitude, and pack them in order to achieve the constant word-length output. In addition, in this pipeline architecture, the VLC codeword and the amplitude can be processed in one clock cycle such that the input data rate of VLC encoder can reach as high as the sampling rate of video/image data. Therefore, it is very suitable for very high data rate video and image compression applications.

The error recovery capability of variable length code (VLC) has been considered as an important performance and design criterion in addition to its coding efficiency. However, almost all of the existing methods for evaluating the error recovery capability of VLC assume that the transmission fault is a random single bit inversion. In this paper, we consider a more generalized problem of precisely evaluating the error recovery capability of VLC in the case that the encoded bit stream is transmitted over a BSC with arbitrary crossover probability. By making use of the Perron-Frobenius Theorem, we derive a very simple expression for the exact mean symbol error rate (MSER) in Levenshtein distance sense. We also prove that in the very low crossover probability region, the mean error propagation length (MEPL) derived for single inversion error case approaches a scaled value of MSER. In addition, we briefly discuss the error recovery of VLC over Gilbert-Elliott channel, which is one of the simplest and practical models for a channel with memory.

In this paper, the frequency scanning and the Modified Universal Variable Length Coding (MUVLC) technique is examined as a means to improve the cell loss resilience of video codecs. An appropriate implementation of this technique for effective use in a pyramid layered coding scheme is described. Simulation results are presented which show the superior performance of this slice based coding technique in comparison to the conventional block scanning and Variable Length Coding (VLC) technique having similar coding efficiency.© (1993) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

We address the optimization of joint source-channel coding schemes for iterative source-channel decoding (ISCD) of first-order Markov sources. The optimization requires source encoders, providing code words with a minimum Hamming distance dmin ges 2. Usually, specifically designed variable- length codes (VLCs) are applied for this purpose, leading, however, to an increased complexity of the decoder. In this paper, we propose a novel concept: a single parity-check code is employed for mapping the quantized source symbols to a binary representation. The additional redundancy introduced by this mapping is afterwards compensated by an inner channel code with rate R > 1. Simulation results for the AWGN channel show that the proposed scheme is superior to VLC- based approaches, while leading to a significantly reduced complexity at the same time.

In multiple-user communications, the bursty nature of the packet arrival times cannot be divorced from the analysis of the transmission process. However, in traditional information theory the random arrival times are smoothed out by appropriated source coding and no consideration is made for the end-to-end delay. In this thesis, using tools from network theory, we investigate simple models that consider the end-to-end delay and/or the variability of the packet arrivals as important parameters, while staying in a information theoretic framework. First, we simplify the problem and focus on the transmission of a bursty source over a single-user channel. We introduce a new measure of channel features that enable us to incorporate the possibility to code among several packets in a scheduling problem. In this setup, we look for policies that minimize the average packet delay. Assuming that the packets are independent and sufficiently large to perform capacity achieving coding, we then consider the problem of allocating rates among a finite number of users communicating through a multiple-user channel. Following the previous work in the context of multiple-access channel, we formulate a scheduling problem in which the rate of each user is chosen from the capacity region of the multiple-user channel. Here, the goal is to find a scheduling policy that minimizes the sum of the transmitter queue lengths, such a policy is called delay optimal. In particular settings, for the additive Gaussian multiple-access channel we show the delay optimality of the Longer Queue Higher Rate policy introduced by Yeh. And, when the users communicate through a symmetric broadcast channel, we propose and show the delay optimality of a Best User Highest Possible Rate policy, among a large class of admissible policies. Finally, in the last part of this thesis, we look at the multiple-user channel coding problem from the perspective of the receivers. By measuring the transmission rates at the receivers, we are able to define variable length codes and to characterize the region of achievable rates when the receivers can decode their intended messages at different instants of time. For the two-user degraded broadcast channel and for the two-user multiple-access channel, we show that the gain in using variable length codes essentially comes from the possibility for the receivers to decode the transmitted messages in non-overlapping periods of time.

Joint source and channel decoding (JSCD) has been proved to be an effective technique which can improve decoding performance by exploiting residual source redundancy. Most previous publications on this subject focus on a traditional coding scheme in which the source variable-length coding (VLC) is serially concatenated with a channel code. In this paper, a parallel concatenated coding scheme for the VLC combined with a turbo code is presented. By merging a symbol-level VLC trellis with a convolutional trellis, we construct a symbol-level joint trellis with compound states. Also, a solution of the symbol-by-symbol a posteriori probability (APP) decoding algorithm based on this joint trellis is derived, which leads to an iterative JSCD approach in the similar way to the classical turbo decoder. The simulation results show that our joint source-channel en/decoding system achieves some gains at the cost of increasing decoding complexity, when compared to the joint iterative decoding based on the bit-level super trellis for the separate coding system.

: The research tasks are: Task 1, Scalable Coding; Task 2, Alternatives to variable length coding (VLC); and Task3, Packetizing for Error Concealment. Initial work on Task 1 built on research from a prior DARPA contract, and resulted in a scalable video coder with the unique property of scalable transmission at six resolution/frame-rate combinations. Task 2 work combined fixed and variable length coding (VLC) into a joint coding approach with distinct robustness advantages, while giving up only a slight amount of performance versus straight VLC coding in the noise-free case. Task 3 Packetzing for Error Concealment explored the new technique dispersive packetization and combined it with error concealment in a state-of-the-art subband/wavelet image coder. An ns-2 network simulation revealed substantial robustness to packet loss error, with useable images recovered under packet loss rates at high as 30%, thus implementing the graceful degradation property.

Since MAP decoding algorithm for variable length codes (VLC) is computational impractical, a fast algorithm is proposed in this paper, which simplifies the trellis representation for VLC so that the number of states is bounded by a constant, thus the computational complexity of the MAP decoding algorithm is significantly reduced, asymptotically from O(n/sup 2/) to O(n). In simulations, only a slight performance degradation of the fast algorithm relative to exact MAP decoding is observed, while it runs about 6 times faster than exact MAP decoding.