用DSP实现MPEG音频层Ⅲ压缩的加速方法

ＭＰＥＧ音频层Ⅲ压缩算法,是由ＩＳＯ１１１７２－３标准规定的一种高效,高保真的压缩编码算法。由于层Ⅲ压缩算法的复杂度高,运算量大,为此提出了在实时应用中,基于数字信号处理器实现层Ⅲ压缩算法的关键运算的加速措施。     

用DSP实现MPEG音频层III压缩的加速方法

MPEG音频层III压缩算法,是由ISO11172-3标准规定的一种高效、高保真的压缩编码算法.由于层III压缩算法的复杂度高,运算量大,为此提出了在实时应用中,基于数字信号处理器(Digital Signal Processor,以下简称DSP)实现层III压缩算法的关键运算的加速措施.     

用DSP实现MPEG音频层II压缩的加速方法

ＭＰＥＧ音频层ＩＩ压缩算法,是由ＩＳＯ１１１７２－３标准规定的一种高效、高保真的压缩编码算法。由于层ＩＩ压缩算法的复杂度高,运算量大,为此提出了在实时应用中,基于数字信号处理器（ＤｉｇｉｔａｌＳｉｇｎａｌＰｒｏｃｅｓｓｏｒ,以下简称ＤＳＰ）实现层ＩＩ压缩算法的关键运算的加速措施。     

用ADSP实现多极化SAR原始数据压缩算法

我们利用自行开发的ADSP21062信号处理板结合多极化合成孔径雷达数据流的特点，采用并行处理方式，实现了一种多极化雷达原始数据的压缩算法。     

基于游程编码的分块交叉数字图像压缩算法

本文在软件工程设计中发现了一种数字图像压缩算法，它是在游程编码基础上的改进和创新，具有许多明显的优点，如无损压缩、高效、快速等。实际应用表明，该算法具有很好的适用性。     

自适应压缩算法（SAC）

片上系统的测试，非常关键的一个问题就是测试数据量的问题。通常片上系统都会包含多个IP内核，而这些内核每一个都需要大量的测试向量来进行测试。这样的测试数据量不仅会超出一般商用自动测试仪器所能提供的存储空间和通道数目，而且也会大大延长测试时间。测试仪器的成本和测试时间是影响测试成本的关键因素。因此对测试数据进行压缩成为一种直接而有效的降低测试成本的手段。现有的测试数据压缩算法大多由其他领域的一些压缩算法衍生而来，而由于测试数据本身具有独特的属性，如可指定性、无序性、不均性等，因此需要根据其特性设计具有更好适应性的压缩算法才能获得更理想的压缩效率和稳定性。本文充分研究了测试数据的特征，提出了变长、不等间距的自适应压缩算法SAC。数学分析方法和实际电路实验分析都表明SAC算法在压缩效率和稳定性方面具有突出的优势。     

一种基于K-均值聚类优化的快速分形图像压缩算法

提出了一种基于K-均值聚类的快速分形图像压缩算法，对搜索窗中的父块和子块，根据其方差的不同，用K-均值聚类方法分别对子块和父块进行聚类，子块只对同一类中的父块进行匹配，从而大大缩短了编码时间。实验结果表明，与经典分形压缩算法相比，本文算法编码速度可提高5倍；同基于方差的快速分形压缩算法相比，本文算法也有明显的优势。     

霍夫曼算法在数字示波器中的应用

针对于数字存储示波器中要存储的波形数据或设置数据比较大，并且用户多用来存储周期波形这一特点，提出了本来用于文件压缩算法的霍夫曼压缩算法，将其改进为应用于数据流压缩。首先描述了用于霍夫曼算法的压缩和解压缩基本原理，并对压缩算法重点讨论，给出了详细的过程，解压过程比较简单，只筒略描述。并对传统的只能对字符进行压缩的霍夫曼算法进行了改进，使之可以完成对数据流压缩。     

基于IEEE802.16e的头压缩的设计与实现

介绍了IEEE802.16e协议中MACCS子层的头压缩机制,并结合MACCS子层的特点,提出了一种IEEE802.16e协议栈开发中MACCS子层头压缩模块的实现方案。通过对已有头压缩算法的研究分析,并结合IEEE802.16e协议的特性提出了一种适合宽带无线通信系统的头压缩算法。     

实用版图压缩算法

本文给出了两种基于约束图的一维版图压缩算法,即完全约束图压缩算法和精简约束图压缩算法,并对两个算法的性能做了讨论;针对版图中较常用的曼哈顿多边形图形,文中还给出了相应的解决办法。     

Ultrasound beamforming using compressed data

The rapid advancements in electronics technologies have made software-based beamformers for ultrasound array imaging feasible, thus facilitating the rapid development of high-performance and potentially low-cost systems. However, one challenge to realizing a fully software-based system is transferring data from the analog front end to the software back end at rates of up to a few gigabits per second. This study investigated the use of data compression to reduce the data transfer requirements and optimize the associated trade-off with beamforming quality. JPEG and JPEG2000 compression techniques were adopted. The acoustic data of a line phantom were acquired with a 128-channel array transducer at a center frequency of 3.5 MHz, and the acoustic data of a cyst phantom were acquired with a 64-channel array transducer at a center frequency of 3.33 MHz. The receive-channel data associated with each transmit event are separated into 8 × 8 blocks and several tiles before JPEG and JPEG2000 data compression is applied, respectively. In one scheme, the compression was applied to raw RF data, while in another only the amplitude of baseband data was compressed. The maximum compression ratio of RF data compression to produce an average error of lower than 5 dB was 15 with JPEG compression and 20 with JPEG2000 compression. The image quality is higher with baseband amplitude data compression than with RF data compression; although the maximum overall compression ratio (compared with the original RF data size), which was limited by the data size of uncompressed phase data, was lower than 12, the average error in this case was lower than 1 dB when the compression ratio was lower than 8.     

Gzip压缩的硬件加速电路设计

硬件无损压缩技术可以发挥专用电路的速度和功耗优势,被广泛应用于大数据计算以及通信领域.本文以GNUzip（Gzip）数据无损压缩技术为原型设计了一种硬件压缩电路.通过采用双Hash函数、并行匹配处理、面向硬件存储的LZ77压缩存储格式、高效数据拼接器等加速方法,发挥并行计算和流水线结构优势,提升压缩速率.该硬件压缩电路基于Verilog HDL设计,使用现场可编程门阵列（FPGA）进行测试和验证.测试数据表明：与软件压缩方式相比,该硬件压缩电路在获得适中压缩率（65.9%）的同时,其压缩速率得到显著提升,平均压缩速率达171Mb/s,满足网络通信、数据存储等实时压缩应用需求.     

Data processing and communication strategies for lifetime optimization in wireless sensor networks

In this paper we introduced a novel Linear Programming framework to model sensor network lifetime when data reduction through compression is utilized. Comparative analysis of three data compression and forwarding strategies show that neither data compression nor flow balancing can achieve the maximal possible sensor network lifetime when optimized independently. The comparisons reveal that jointly optimizing data compression and load balancing results in up to an order of magnitude longer network lifetimes than non-optimized data compression and load balancing.     

二维电能质量数据压缩

近年来,大量电能质量监测点的建立,使得电能质量数据增加,为处理大量的电能质量监测数据,提出了一种基于方向小波变换的电能质量数据压缩方法.将一维的电能质量数据转换成二维的数据,得到经过此变换分解的二维数据的小波系数,再将这些小波系数应用图像压缩中的SPIHT（多级树集合分裂）编码算法,压缩二维表示的电能质量数据.实验结果表明,此方法具有压缩率高、速度快,控制压缩比和特征不变的特点,有利于根据网络的状况调节传输的数据量.     

ECG data compression techniques-a unified approach

A broad spectrum of techniques for electrocardiogram (ECG) data compression have been proposed during the last three decades. Such techniques have been vital in reducing the digital ECG data volume for storage and transmission. These techniques are essential to a wide variety of applications ranging from diagnostic to ambulatory ECG's. Due to the diverse procedures that have been employed, comparison of ECG compression methods is a major problem. Present evaluation methods preclude any direct comparison among existing ECG compression techniques. The main purpose of this paper is to address this issue and to establish a unified view of ECG compression techniques. ECG data compression schemes are presented in two major groups: direct data compression and transformation methods. The direct data compression techniques are: ECG differential pulse code modulation and entropy coding, AZTEC, Turning-point, CORTES, Fan and SAPA algorithms, peak-picking, and cycle-to-cycle compression methods. The transformation methods briefly presented, include: Fourier, Walsh, and K-L transforms. The theoretical basis behind the direct ECG data compression schemes are presented and classified into three categories: tolerance-comparison compression, differential pulse code modulation (DPCM), and entropy coding methods. The paper concludes with the presentation of a framework for evaluation and comparison of ECG compression schemes.     

A Twin Symbol Encoding Technique Based on Run‐Length for Efficient Test Data Compression

Recent test data compression techniques raise concerns regarding power dissipation and compression efficiency. This letter proposes a new test data compression scheme, twin symbol encoding, that supports block division skills that can reduce hardware overhead. Our experimental results show that the proposed technique achieves both a high compression ratio and low‐power dissipation. Therefore, the proposed scheme is an attractive solution for efficient test data compression.     

Sensor data compression based on MapReduce简

A compression algorithm is proposed in this paper for reducing the size of sensor data. By using a dictionary-based lossless compression algorithm, sensor data can be compressed efficiently and interpreted without decompressing. The correlation between redundancy of sensor data and compression ratio is explored. Further, a parallel compression algorithm based on MapReduce [1] is proposed. Meanwhile, data partitioner which plays an important role in performance of MapReduce application is discussed along with performance evaluation criteria proposed in this paper. Experiments demonstrate that random sampler is suitable for highly redundant sensor data and the proposed compression algorithms can compress those highly redundant sensor data efficiently.     

雷达数据有损压缩综述

雷达信号的数据量非常庞大,如果不压缩进行存储或传输,会占用很大资源。文中介绍了雷达信号的特点,对常用的雷达数据压缩方法进行了分类,给出了评价指标。介绍了雷达有损压缩中较为典型的游程、单触发单元、离散余弦变换、小波分析等压缩算法,阐述了各算法的流程和关键技术,并结合评价指标进行了比较,提出了建议的压缩方法。文中将压缩流程扩展为去噪声和压缩2个部分,充分肯定了去噪在雷达数据压缩中的作用,得出了一些有意义的结论。     

基于离散余弦变换的图像压缩研究

图像压缩是数据压缩技术在数字图像上的应用,其目的是减少图像数据中的冗余信息,从而用更加高效的格式存储和传输数据。图像压缩可以是有损数据压缩也可以是无损数据压缩。这里所研究的是有损压缩技术,对于此类技术,变换编码是最常用的方法,如离散余弦变换（DCT）或者小波变换这样的傅里叶相关变换,然后进行量化和用熵编码法压缩。     

基于DPCM-Huffman压缩算法的图像传感器去暗电流系统

为了解决图像传感器暗电流消除过程中数据存储问题,本文提出了一种基于DPCM-Huffman压缩算法的数据压缩去暗电流系统并进行硬件实现;在该系统工作之前,首先通过DPCM与Huffman组合压缩算法将图像传感器暗电流数据进行编码压缩,并将压缩后的数据存储于FLASH存储器中。而后在图像传感器工作过程中,通过读取存储器中数据,进行Huffman与DPCM解码,最终消除图像传感器中的暗电流。实验证明,采用该压缩去暗电流系统处理后,以分辨率为256×256的CMOS图像传感器为例,压缩后数据压缩比为3.12,数据量降为原始数据的32%,提高3倍的工作速度。实践证明,本文提出的解压系统提高了数据压缩比,保证了数据精度,提高了图像传感器的工作速度,是一种适用于CMOS图像传感器暗电流消除的压缩系统。