An Algorithm for Vector Quantizer Design

An efficient and intuitive algorithm is presented for the design of vector quantizers based either on a known probabilistic model or on a long training sequence of data. The basic properties of the algorithm are discussed and demonstrated by examples. Quite general distortion measures and long blocklengths are allowed, as exemplified by the design of parameter vector quantizers of ten-dimensional vectors arising in Linear Predictive Coded (LPC) speech compression with a complicated distortion measure arising in LPC analysis that does not depend only on the error vector.     

The Minimum Average Code for Finite Memoryless Monotone Sources

The problem of selecting a code for finite monotone sources with N symbols is considered. The selection criterion is based on minimizing the average redundancy (called Minave criterion) instead of its maximum (i.e., Minimax criterion). The average probability distribution P^Nmacr, whose associated Huffman code has the minimum average redundancy, is derived. The entropy of the average distribution (i.e., H(P^Nmacr)) and the average entropy of the monotone distributions (i.e., H(P^Nmacr)) are studied. It is shown that both logN-H(P^Nmacr) and logN-H(P^Nmacr) are asymptotically equal to a constant (sime0.61). Therefore, there is only a negligible penalty (at most 1.61 bits/symbol) in using a simple fixed-length code with respect to the optimal code. An efficient near-optimal encoding technique is also proposed. The consequences of the two approaches, i.e., Minave and Minimax, are compared in terms of their associated distributions and associated codes. In order to evaluate the average performance of the Minimax code, we prove that the informational divergence of the average distribution and Minimax distribution asymptotically grows as -2.275+loglogN     

Forward Adaptive Logarithmic Quantizer with New Lossless Coding Method for Laplacian Source

The aim of this paper is to improve the G.711 standard, which is widely used, especially in the public switched telephone network (PSTN). Two solutions are proposed. The first solution uses only lossless coder, achieving a bit-rate decrease of 0.82 bits/sample, compared to the G.711 codec. The second solution uses forward adaptation and a lossless coder, further decreasing the bit-rate (by 1.25 bits/sample) and achieving higher average signal-to-quantization noise ratio (SQNR) in comparison with the G.711 codec. Also, the second solution is more robust than the G.711 codec, which means that it has near constant SQNR for a wide range of input signal power. That is very important for signals whose input power varies with time, such as speech and video signals. Our solutions are compatible with the G.711 codec, they have little additional complexity and delay and therefore can be applied in real-time systems, such as PSTN or VoIP. They can also be used in many other systems, such as WiMax and OFDM, as a replacement or improvement of the G.711 codec. Standardization process of the G.711.1 standard (which is a wide-band extension of the G.711 standard) is largely present. Our solutions fulfill all the requirements for that new standard; therefore they can be implemented in its low-frequency part.     

宽带ISF参数的转换分类乘积码锥形矢量量化

本文提出了一种新的应用于宽带导抗谱频率参数量化的转换分类乘积码锥形矢量量化方案.该量化器基于转换分类与乘积码锥形矢量量化原理,首先对待量化的ISF参数矢量进行分类,然后按类进行乘积码锥形矢量量化.该算法具有低存储量及低复杂度的特点.实验表明,该算法在每帧编码比特数为46时,平均谱失真比乘积码锥形矢量量化低,且达到了透明量化标准.     

基于快速胞腔划分的改进分裂法矢量量化码书设计

本文提出了基于快速胞腔划分的改进分裂法语音信号矢量量化码书设计新算法。新算法应用特征变量对码书进行合理的构造，使得码书在结构上具有秩序性。利用这种秩序性进行快速划分胞腔，从而压缩分裂法码书训练中庞大的运算量。计算机实验结果表明，新算法明显减少了码本训练的复杂度，提高了矢量量化码书的训练速度。实验还分析了码书扩展参数r的不同取值对码书性能的影响．     

序号预测矢量量化器及其在图象编码中应用

本文提出一种序号预测矢量量化器的结构，与一般矢量量化器相比，它充分利用了图象极强的二维相关特性，并采用预测的方法去除冗余码字，从而在保证译码图象质量与一般矢量量化器的译码图象质量相同的前提下，压缩比可提高一倍以上。     

宽带ISF参数的非等系数帧间预测分裂矢量量化方法

 本文提出了一种新的适用于宽带语音编码ISF参数量化的非等系数帧间预测分裂矢量量化方案.该量化方案利用ISF参数的帧间相关性,基于预测分裂矢量量化原理,首先对待量化的ISF参数矢量进行去均值和非等系数帧间预测,然后对去均值后的ISF参数的预测残差进行分裂矢量量化.实验表明,该算法在每帧编码比特数为46bits时达到了透明量化,且平均谱失真比G.722.2中ISF参数量化的平均谱失真小.     

基于人工神经网络的语音多脉冲激励矢量量化器的设计及其性能分析

本文讨论了人工神经网络技术在语音压缩编码方面的应用,提出了一种用Kohonen网络实现语音多脉冲激励分析模型的矢量量化方法。该方法将参数分析和量化编码熔为一体,和传统的先分析、后量化方法相比较,具有许多优良的特性,如全并行处理、过程简化等。本文针对语音多脉冲激励模型,提出了量化网络的结构和学习规则,并将此方法和传统方法进行了比较。最后对网络的压缩性能进行了计算机模拟,结果表明应用人工神经网络进行语音信源的压缩是切实可行的。     

A Robust Hidden Markov Gauss Mixture Vector Quantizer for a Noisy Source

Noise is ubiquitous in real life and changes image acquisition, communication, and processing characteristics in an uncontrolled manner. Gaussian noise and Salt and Pepper noise, in particular, are prevalent in noisy communication channels, camera and scanner sensors, and medical MRI images. It is not unusual for highly sophisticated image processing algorithms developed for clean images to malfunction when used on noisy images. For example, hidden Markov Gauss mixture models (HMGMM) have been shown to perform well in image segmentation applications, but they are quite sensitive to image noise. We propose a modified HMGMM procedure specifically designed to improve performance in the presence of noise. The key feature of the proposed procedure is the adjustment of covariance matrices in Gauss mixture vector quantizer codebooks to minimize an overall minimum discrimination information distortion (MDI). In adjusting covariance matrices, we expand or shrink their elements based on the noisy image. While most results reported in the literature assume a particular noise type, we propose a framework without assuming particular noise characteristics. Without denoising the corrupted source, we apply our method directly to the segmentation of noisy sources. We apply the proposed procedure to the segmentation of aerial images with Salt and Pepper noise and with independent Gaussian noise, and we compare our results with those of the median filter restoration method and the blind deconvolution-based method, respectively. We show that our procedure has better performance than image restoration-based techniques and closely matches to the performance of HMGMM for clean images in terms of both visual segmentation results and error rate.     

恒虚警慢门限量化器的理论与应用设计

根据恒虚警慢门限的理论,讨论了量化门限间接随噪声电平变化保持恒虚警的必要性及恒虚警慢门限噪声采样区的自动有效判别问题,提出了一种新在和复杂环境下采样区的自动有效判别及门限自动调整方案。     

Low-Resolution Scalar Quantization for Gaussian Sources and Absolute Error

This correspondence considers low-resolution scalar quantization for a memoryless Gaussian source with respect to absolute error distortion. It shows that slope of the operational rate-distortion function of scalar quantization is infinite at the point D_max where the rate becomes zero. Thus, unlike the situation for squared error distortion, or for Laplacian and exponential sources with squared or absolute error distortion, for a Gaussian source and absolute error, scalar quantization at low rates is far from the Shannon rate-distortion function, i.e., far from the performance of the best lossy coding technique     

二项分布—拉普拉斯和离散的高斯—拉普拉斯边缘检测算子的 性能

本文从空域及频域两方面对二项分布——拉普拉斯(LOB)及离散的高斯——拉普拉斯(DLOG)边缘检测算子进行了分析比较.在两种算子的尺度空间常数很大时,它们的时域和频域特性及对图象进行边缘检测的性能是基本相同的.但当尺度空间常数较小时,从它们在频域中带通特性的中心频率、3分贝带宽及截止频率处的高频衰减性能进行比较可知,LOB算子稍优于离散的LOG算子.故LOB算子可看成是LOG算子的一种离散实现.文中给出了实验结果,证明了分析结果的正确性.     

Vector Quantizers and Predictive Quantizers for Gauss-Markov Sources

Low-rate vector quantizers are designed and simulated for highly correlated Gauss-Markov sources and the resulting performance is compared with Arnstein's optimized predictive quantizer and with Huang and Schultheiss' optimized transform coder. Two implementations of vector quantizers are considered: full search vector quantizers-which are optimal but require large codebook searches-and tree searched vector quantizers-which are suboptimal but require far less searching. The various systems are compared on the basis of performance, complexity, and generality of design techniques.     

MPEG－2视频编码的自适应量化器设计

本文在研究ＭＰＥＧ－２ＴＭ５建议的自适应量化策略的基础上，设计了一种新的自适应量化器。以块为基础分析宏块的局部视觉活动特性，并通过综合评价宏块中各块的视觉活动特性来最终决定自适应视觉量化因子。实验结果表明，本文所设计的自适应量化器能均匀分布图像编码主观失真，改善了图像质量，特别是减少了平坦区的块效应，降低了平坦区强边缘的失真。     

ISO 14443单芯片读卡机放大、滤波和量化电路的设计

介绍了ISO 14443解调电路解调后滤波、放大和量化电路的设计,提出了一种新的阈值电压可变的比较器结构.电路经O.6μm工艺生产线流片验证,测试结果显示:电路可在2.5～5.5V电压范围内工作,工作温度为-20～80℃,载波信号衰减大于40dB,电路增益在26～44dB范围内可调,5V条件下,电路的功耗小于10mA.     

ISO 14443单芯片读卡机放大、滤波和量化电路的设计

介绍了ISO 14443解调电路解调后滤波、放大和量化电路的设计,提出了一种新的阈值电压可变的比较器结构. 电路经0.6μm工艺生产线流片验证,测试结果显示：电路可在2.5～5.5V电压范围内工作,工作温度为-20~80℃,载波信号衰减大于40dB,电路增益在26~44dB范围内可调,5V条件下,电路的功耗小于10mA.     

Frequency domain design of FIR and IIR Laplacian of Gaussian filters for edge detection

This work addresses the design of LoG filters in the frequency domain within a structure formed by the cascade of quasi-Gaussian and discrete Laplacian filters. The main feature of such a structure is that it requires half the number of convolutions of the classical structure in which the LoG transfer function is expressed as the sum of two separable transfer functions of 1-D Gaussian and LoG type. Such a perspective allows one to rephrase the design of IIR and FIR filters for edge detection as a frequency domain approximation problem solvable by standard digital filter design tools. The zero-phase IIR solutions have a good performance at low orders and approximation errors practically independent of the aperture parameter. The characteristics of the nearly linear-phase IIR filters solving the problem suggest the consideration of linear-phase FIR filters with zeros constrained on the unit circle. The use of such filters leads to remarkable computational savings with respect to the filters designed by impulse response sampling. The agreement between the edge values obtained by the filters designed according to the scheme proposed in this work and those obtained by standard techniques is very good.Work carried out with the financial support of the C.N.R.-Progetto Finalizzato Robotica, contract no. 91.01942.PF67.     

广义高斯信源的自适应编码研究

首先介绍了当前最新的几种视频编码标准并且进行了比较,熵编码是每一个视频编码标准必须认真研究的课题,为了减少由于失配所带来的效率损失,本文提出了一种自适应编码技术:自适应指数哥伦布码,并与自适应算术编码进行了比较.分析和仿真都表明即使信源特性在大范围内发生变化,自适应指数哥伦布码对于保持高的编码效率是足够稳健的(90%以上的情况),同时保持了指数哥伦布码和哥伦布-莱期码的简洁性.     

Uniform and piecewise uniform lattice vector quantization formemoryless Gaussian and Laplacian sources

Lattice vector quantizer design procedures for nonuniform sources are presented. The procedures yield lattice vector quantizers with excellent performance and retaining the structure required for fast quantization. Analytical methods for truncating and scaling lattices to be used in vector quantizations are given, and their utility is demonstrated for independent and identically distributed (i.i.d.) Gaussian and Laplacian sources. An analytical technique for piecewise linear multidimensional compandor designs is evaluated for i.i.d. Gaussian and Laplacian sources by comparing its performance to that of the other vector quantizers     

逆伽马纹理复合高斯杂波参数的贝叶斯估计方法

复合高斯杂波(CGC)在拟合高分辨力、低掠射角海杂波中已得到广泛应用,带有逆伽马纹理的CGC的强度分布为广义帕累托(GP)分布。在实际雷达工作场景中,由于观测区域内海杂波的非平稳非均匀特性,导致独立同分布杂波样本的获取十分困难。提出一种广义帕累托分布参数的贝叶斯估计方法,通过在线更新数据的先验信息,获取小样本情形下GP分布参数。仿真实验证明,该方法能够在样本数量较小的情况下,对GP数据实现较为精确的参数估计。