二维网格编码矢量量化及其在静止图像量化中的应用

该文提出了在二维码书空间中，在矢量量化（VQ）的基础上，应用网格编码量化（TCQ）的思想来实现量化的新方法－－二维网格编码矢量量化（2D－TCVQ）。该方法首先把小码书扩展成大的虚码书，然后用网格编码矢量量化（TCVQ）的方法在扩大的二维码书空间中用维物比算法来寻找最佳量化路径。码书扩大造成第一子集最小失真减小从提高了量化性能。由于二维TCVQ采用的码书尺寸较小，因而可以应用到低存贮、低功耗的编解码环境。仿真结果表明，同一码书尺寸下，二维TCVQ比TCVQ好0．5dB左右。同时，该方法具有计算量适中，解码简单以及对误差扩散不敏感的优点。     

一种基于优先树脉冲取代的固定码本搜索方法

分析了G.722.2中的固定码本结构及其搜索方法,结合深度优先树与脉冲取代法各自的优点,提出了一种新的方法——基于优先树脉冲取代的固定码本搜索方法,该方法在基本保持语音质量的前提下,可使固定码本搜索计算复杂度降低,从而使G.722.2的编码运行时间进一步减少。实验结果表明,与G.722.2中采用的深度优先树搜索方法相比,基于优先树脉冲取代的固定码本搜索方法可以在不影响语音质量的前提下,使固定码本搜索复杂度降低85%以上。     

Effect of ordering the codebook on the efficiency of the partialdistance search algorithm for vector quantization

Recently, C.D. Bei and R.M. Gray (1985) used a partial distance search algorithm that reduces the computational complexity of the minimum distortion encoding for vector quantization. The effect of ordering the codevectors on the computational complexity of the algorithm is studied. It is shown that the computational complexity of this algorithm can be reduced further by ordering the codevectors according to the sizes of their corresponding clusters     

On reducing computational complexity of codebook search in CELPcoding

A computationally efficient codebook search method in code-excited linear prediction is proposed. The method can reduce the computational complexity by almost one half compared to the frequency-domain codebook search method that is currently regarded as the fastest search method, while giving almost the same quality of speech. This reduction is possible as a result of the simultaneous use of frequency-domain search and code vector sparsity     

A fast exact GLA based on code vector activity detection

This paper introduces a new method for reducing the number of distance calculations in the generalized Lloyd algorithm (GLA), which is a widely used method to construct a codebook in vector quantization. Reduced comparison search detects the activity of the code vectors and utilizes it on the classification of the training vectors. For training vectors whose current code vector has not been modified, we calculate distances only to the active code vectors. A large proportion of the distance calculations can be omitted without sacrificing the optimality of the partition. The new method is included in several fast GLA variants reducing their running times over 50% on average.     

Dynamic partial search scheme for stochastic codebook of FS1016CELP coder

The authors present a new classified dynamic partial search structure for the stochastic codebook of the FS1016 CELP coder to replace the fixed partial search for selecting the best excitation vector of the stochastic codebook. In the proposed scheme, the conventional one-stage stochastic codebook search is substituted with a two-stage dynamic method for reducing the computational complexity without degrading the voice quality. The establishment of this structure is based on two classifiers, one for the line spectrum pairs (LSP) of the input signals, and the other for the autocorrelation coefficients (AC) of the stochastic codebook search target. In addition, the stochastic codebook is classified into K subcodebooks, and with these two classifiers it is possible to determine dynamically which subcodebook needs to be searched. This method achieves a reduction in the search procedure by a factor of 2-8. The efficiency of these two classifiers is discussed and the comparison of the performance between the fixed partial search and the proposed technique is also addressed     

Fast search algorithms for vector quantization of images usingmultiple triangle inequalities and wavelet transform

The encoding of vector quantization (VQ) needs expensive computation for searching the closest codevector to the input vector. This paper presents several fast encoding algorithms based on multiple triangle inequalities and wavelet transform to overcome this problem. The multiple triangle inequalities confine a search range using the intersection of search areas generated from several control vectors. A systematic way for designing the control vectors is also presented. The wavelet transform combined with the partial distance elimination is used to reduce the computational complexity of the distance calculation of vectors. The proposed algorithms provide the same coding quality as the full search method. The experimental results indicate that the new algorithms perform more efficiently than existing algorithms.     

Fast vector quantization algorithms based on nearest partition set search.

A fast search method for vector quantization is proposed in this paper. It makes use of the fact that in the generalized Lloyd algorithm (GLA) a vector in a training sequence is either placed in the same minimum distance partition (MDP) as in the previous iteration or in a partition within a very small subset of partitions. The proposed method searches for the MDP for a training vector only in this subset of partitions plus the single previous MDP. As the size of this subset is much smaller than the total number of codevectors, the search process is speeded up significantly. The creation of the subset is essential, as it has a direct effect on the improvement in computation time of the proposed method. The schemes that create the subset efficiently have been proposed. The proposed method generates a codebook identical to that generated using the GLA. It is simple and requires only minor modification of the GLA and a modest amount of additional memory. The experimental results show that the computation time of codebook training was improved by factors from 6.6 to 50.7 and from 5.8 to 70.4 for two test data sets when codebooks of sizes from N = 16 to 2048 were trained. The proposed method was also combined with an earlier published method to further improve the computation time.     

基于空间组合矢量分类的小波图像网格编码矢量量化

本文基于零树编码、矢量分类和网格编码量化的思想,提出了对小波图像采用空间矢量组合和分类后进行网格编码矢量量化的新方法.该方法充分利用了各高频子带系数频率相关性和空间约束性,依据组合矢量能量和零树矢量综合判定进行分类,整幅图像只需单一量化码书,分类信息占用比特数少.对重要类矢量实行加权网格编码矢量量化,利用卷积编码扩展信号空间以增大量化信号间的欧氏距离,用维特比算法搜索最优量化序列,比使用矢量量化提高了0.6db左右.该方法编码计算复杂度适中,解码简单,可达到很好的压缩效果.     

SCMA codebook design based on resource block constellation

Aiming at the problems of typical sparse code multiple access codebook design scheme based on multidimensional mother constellation that the complexity is high and the minimum Euclidean distance between constellation points on resource blocks is difficult to determine,a SCMA codebook design scheme based on resource block constellation was proposed.By converting the design of multidimensional mother constellation into the design of two-dimensional resource block constellation,the design complexity of constellation was reduced.And the codebook design scheme starting from resource block constellation could maximize the minimum Euclidean distance between constellation points on resource blocks,which was better than the design method in which user codebooks were obtained from multi-dimensional mother constellation.Simulation results show that the proposed SCMA codebook design scheme based on resource block constellation can significantly improve the BER performance of system compared with the typical codebook design scheme based on multidimensional mother constellation.     

Fast sequential implementation of “neural-gas” networkfor vector quantization

Although the “neural-gas” network proposed by Martinetz et al. in 1993 has been proven for its optimality in vector quantizer design and has been demonstrated to have good performance in time-series prediction, its high computational complexity (NlogN) makes it a slow sequential algorithm. We suggest two ideas to speedup its sequential realization: (1) using a truncated exponential function as its neighborhood function and (2) applying a new extension of the partial distance elimination method (PDE). This fast realization is compared with the original version of the neural-gas network for codebook design in image vector quantization. The comparison indicates that a speedup of five times is possible, while the quality of the resulting codebook is almost the same as that of the straightforward realization     

基于贪心策略的大规模MIMO系统信号检测算法

针对传统球形译码性能和计算复杂度受到初始半径及搜索策略制约的问题,提出了一种新的基于M算法的贪心策略球形译码检测算法,对树搜索的方法进行了改进,先将该层信号集合中的距离增量进行排序,然后选择距离增量最小的M个点为信号点,这样每一次选取的信号点相对该层都是局部最优的.仿真结果表明,相比于传统球形译码检测算法,当M为1时,该算法可以降低约30％的计算复杂度.使球形译码算法的效率得到了很大的提高,可以运用于大规模MIMO系统中.     

Fast codevector search scheme for 3D mesh model vector quantisation

A new fast approach to the nearest codevector search for 3D mesh compression using an orthonormal transformed codebook is proposed. The algorithm uses the coefficients of an input vector along a set of orthonormal bases as the criteria to reject impossible codevectors. Compared to the full search algorithm, a great deal of computational time is saved without extra distortion and additional storage requirement. Simulation results demonstrate the effectiveness of the proposed algorithm in terms of computational complexity.     

A fuzzy classified vector quantizer for image coding

Vector quantization of images raises problems of complexity in codebook search and subjective quality of images. The family of image vector quantization algorithms proposed in this paper addresses both of those problems. The fuzzy classified vector quantizer (FCVQ) is based on fuzzy set theory and consists basically in a method of extracting a subcodebook from the original codebook, biased by the features of the block to be coded. The incidence of each feature on the blocks is represented by a fuzzy set that captures its (possibly subjective) nature. Unlike the classified vector quantizer (CVQ), in the FCVQ a specific subcodebook is extracted for each block to be coded, allowing a better adaptation to the block. The CVQ may be regarded as a special case of the FCVQ. In order to explore the possible correlation between blocks, an estimator for the degree of incidence of features on the block to be coded is included. The estimate is based on previously coded blocks and is obtained by maximizing a possibility; a distribution that intends to represent the subjective knowledge on the feature's possibility of occurrence conditioned to the coded blocks is used. Some examples of the application of a FCVQ coder to two test images are presented. A slight improvement on the subjective quality of the coded images is obtained, together with a significant reduction on the codebook search complexity and, when applying the estimator, a reduction of the bit rate     

Efficient algebraic code-excited linear predictive codebook search

To reduce the computational complexity of algebraic code-excited linear prediction (ACELP) coders, an efficient codebook search mechanism based on a simplified correlation matrix (SCM) of the vocal impulse response is proposed. In the proposed approach, the statistical characteristics of the vocal impulse response are identified such that only a small proportion of the total number of correlation coefficients in the correlation matrix need be calculated before the ACELP search procedure is carried out. Furthermore, the proposed joint scheme, by combining the SCM method and a pulse position prediction scheme, not only decreases the arithmetic complexity in the pre-computing autocorrelation matrix but also reduces the number of pulse position combinations. The simulation and experimental results show that the proposed method provides an effective reduction in the computational load of the ACELP codebook search procedure with no discernible degradation of the speech quality     

Minimax partial distortion competitive learning for optimalcodebook design

The design of the optimal codebook for a given codebook size and input source is a challenging puzzle that remains to be solved. The key problem in optimal codebook design is how to construct a set of codevectors efficiently to minimize the average distortion. A minimax criterion of minimizing the maximum partial distortion is introduced in this paper. Based on the partial distortion theorem, it is shown that minimizing the maximum partial distortion and minimizing the average distortion will asymptotically have the same optimal solution corresponding to equal and minimal partial distortion. Motivated by the result, we incorporate the alternative minimax criterion into the on-line learning mechanism, and develop a new algorithm called minimax partial distortion competitive learning (MMPDCL) for optimal codebook design. A computation acceleration scheme for the MMPDCL algorithm is implemented using the partial distance search technique, thus significantly increasing its computational efficiency. Extensive experiments have demonstrated that compared with some well-known codebook design algorithms, the MMPDCL algorithm consistently produces the best codebooks with the smallest average distortions. As the codebook size increases, the performance gain becomes more significant using the MMPDCL algorithm. The robustness and computational efficiency of this new algorithm further highlight its advantages.     

Jointly optimized trellis-coded residual vector quantization

The union of residual vector quantization (RVQ) and trellis-coded vector quantization (TCVQ) was considered by various authors where the emphasis was on the sequential design. We consider a new jointly optimized combination of RVQ and TCVQ with advantages in all categories. Necessary conditions for optimality of the jointly optimized trellis-coded residual vector quantizers (TCRVQ) are derived. A constrained direct sum tree structure is introduced that facilitates RVQ codebook partitioning. Simulation results for jointly optimized TCRVQ are presented for memoryless Gaussian, Laplacian, and uniform sources. The rate-distortion performance is shown to be better than RVQ and sequentially designed TCRVQ     

Fast codebook search algorithm for unconstrained vectorquantisation

Vector quantisation (VQ) is a well known data compression technique which maps an ordered set of real numbers into a single integer. However, it is difficult to achieve accurate compression with the use of unconstrained Voronoi VQ when the codebook level and vector dimensionality are very large, due to the extremely high real-time computational complexity involved in full codebook search. To overcome this difficulty, a classified pre-selection method is proposed. Compared to the conventional full search method, the algorithm reduces the computational complexity involved in the code vector selection procedure by 70%~90% with almost no loss in coder performance, at the cost of only a slight increase in the storage requirement     

一种基于G.729的CS-ACELP新算法

在G．729的基本框架下,码本搜索采用次最优部分码本快速搜索法,知觉加权滤波器使用基于声学心理模型的知觉加权滤波器,使得8Kb／s共扼结构代数码激励线性预测语音编码在不降低语音质量的情况下降低计算复杂度。次最优部分码本快速搜索方法虽然降低搜索准确度,但是大大减小了搜索时的数据处理量;声学心理滤波器考虑人耳对不同频率信号的不同敏感度,因而能获得更好的主观音质效果。仿真结果表明,该算法复杂度降低,并取得满意的合成语音质量。     

A vector quantizer with minimum visible distortion

A method for designing codebooks for vector quantization (VQ) based on minimum error visibility in a reconstructed picture is described. The method uses objective measurements to define visibility for the picture being coded. The proposed VQ is switched type, i.e., the codebook is divided into subcodebooks, each of which is related to a given subrange of error visibility. Codebook optimization is carried out on the basis of a particular definition of visible distortion of the reconstructed image. Subjective judgment of the test results, carried out at 0.5 b/pel bit rate, indicates that the proposed VQ enables low-distortion images to be reconstructed even when subcodebooks with a small number of codewords are used, thus reducing the codebook search time to about 10% of that required by a fixed VQ (both inside and outside the training set)