基于整数小波变换的实时图像压缩编码算法

随着数字图像压缩编码技术的广泛应用,人们对于压缩编码技术的实时性要求越来越高,如何进行快速有效的图像压缩编码是当前需要解决的关键技术。文中在分析提升算法和基于提升算法的整数小波变换的基础上,介绍了一种新的基于整数小波变换和树特征平面的数字图像编码方法,该算法只需对小波系数进行一次扫描即可完成编码过程,简单易行。实验证明该算法性能优良,并且与零树编码相比大大节约了处理时间。     

空时自适应处理的通用平台设计与实现

该文利用多个高性能数字信号处理器,结合FPGA和通用处理器,实现了一个空时自适应处理(STAP)的通用实时平台系统。借鉴Valiant(1990)提出的BSP模型, 采用多重流水线,提出一个空时自适应处理(STAP)计算模型。该模型可以弥补STAP算法和实际并行系统的差距,为开发提供了统一框架;同时,方便了对算法的性能评估。在基于该模型的具体开发过程中,选择可扩展簇式多处理机结构作为系统硬件架构,采用数据块静态分配方案进行算法的分解与映射,并采取一系列通信和程序优化的方法。结果表明,系统能满足实时要求,可扩展性好,方便类似系统的系列开发。     

Real-Time Speech Coding

This paper reviews our recent efforts in the design and implementation of real-time speech coders. We discuss our approach and methodology for real-time hardware for coder techniques ranging from low to high complexity. Examples of realizations are given for each approach. They include adaptive differential PCM coding, subband coding, harmonic scaling with subband coding, and adaptive transform coding. Low to medium complexity techniques are based on the use of the Bell Laboratories digital signal processing (DSP) integrated circuit. High complexity block processing techniques are based on the use of an array processing computer. We conclude with an assessment of the performance versus complexity tradeoffs involved in these coding methods.     

基于静止图像的小波图像编码

小波图像编码是近十几年发展起来的一种新兴的图像编码方法，目前对其研究较为广泛。主要介绍了当前基于静止图像的小波编码的原理、基本特性、现有方法和发展前景，以及所存在的问题。希望以此进一步推动这一前沿领域的研究工作。     

Real-Time Hadamard Transform Coding for TV Signals

Analog and digital schemes for implementing the onedimensional Hadamard transform in real time for TV signals has been proposed. Within practical limitations, hardware has been developed and tested according to the scheme. The evaluation of the hardware has been carried out using a real image. Furthermore, bandwidthreduction experiments are conducted for various bit rates. Analog and digital transform coding schemes are compared for prominent performance parameters. It is demonstrated that good broadcast and video-phone quality pictures can be obtained using the first four coefficients, and the first two coefficients, respectively.     

A Novel Adaptive Algorithm for Real-Time Image Enhancement

Aiming at the limitation of the traditional algorithm of unsharp masking for image enhancement, we deduce the function to get the coefficient for controlling image enhancement based on the unsharp masking and Gaussian operator. Then we propose a novel adaptive algorithm for real-time image enhancement, and analyze the way for realizing the algorithm by hardware. At last contradistinctive experimental results are given of the algorithm and other algorithms for image enhancement. The results show that we can enhance detail regions of image to the greatest extent, avoid excessive overshoot in edge regions, and minimize the degree of enhancement in uniform regions. A pleasant result is achieved by using the proposed algorithm. Furthermore, it can be realized simply by hardware. Accordingly, we can enhance image effectively to satisfy real-time demand.     

一种用于图像分类的语义增强线性编码方法

针对传统编码模型中存在的编码歧义性问题,该文提出一种考虑特征上下文的语义增强线性编码方法。首先,通过学习局部邻域中特征共生关系矩阵来表示上下文信息。然后,在编码过程中同时引入学习而得的上下文信息与特征上下文匹配权重得到语义增强编码模型。由于上下文信息与上下文匹配权重的功能,使得此编码方法不仅丰富了编码的语义信息,还能够有效避免噪声带来的影响。在3个基准数据集(Scene15, Caltech101以及 Caltech256)上充分的实验验证了该方法的有效性。     

模型基辅助编码中实时运动估计的自适应方法

在长序列运动估计中,常用的预测最小均方力法(PLS、MPLS)和扩展的卡尔曼滤波方法(EKF)对误差敏感,鲁棒性差。本文提出一种新的自适应实时三维运动估计方法(MEKF):即设计一个实时自适应调整参数的扩展卡尔曼滤波进行运动估计,然后对其经过数据处理,消除估计的振荡误差。文中还将该方法与前三种估计方法进行了模拟和真实序列实验的对比,实验结果表明本文所提出的估计方法具有很好的稳定性利很高的精度。     

机动目标的逆合成孔径雷达成像原理与算法

对于非合作的机动目标,由于目标相对于雷达射线的姿态和转速难以测定,而且是时变的,因而给逆合成孔径雷达(ISAR)成像造成较大困难.本文讨论了这种情况下成像的一般原理,并对机动性不太大,散射点子回波多普勒变化满足一阶近似条件时,提出了实用算法.实测数据的处理结果说明新算法是可行的.     

A Novel R-D Optimized MB-level Rate Control Scheme for Real-Time Video Coding

Rate control has a critical influence on the video encoder design, and MB-level rate control is more flexible to control the spatial coding performance. However, most existing MB-level rate control methods are not designed for hardware implementation, and are too complex for practical use in real-time video coding. In this paper, a simple and effective MB-level rate control scheme is proposed that uses historical rate information to directly assign a QP value to a class of MBs. This paper will also introduce a method to realize the idea and make the pipeline data dependency applicable in circuit design. Experiments show that the proposed classification-based MB-level rate control algorithm can achieve a coding gain up to 0.6 dB and an averaging gain of 0.18 dB.     

一种新的图像实时放大技术

该文提出了一种视频图像整数倍放大的实时插值方案一改进的像素填充插值法,给出了其基本原理及软、硬件实现方法.与重复插值法、线性插值法、像素填充插值法和小波放大法等进行了比较,并给出了放大后图像的主观和客观评价。结果表明改进的像素填充插值法的效果明显优于其他实时放大方法,且其硬件实现并不复杂,可用于视频图像实时放大的软、硬件设计。     

A Linear Systolic Array for Real-Time Morphological Image Processing

Mathematical morphology has proven to be a very useful tool for applications such as smoothing, image skeletonization, pattern recognition, machine vision, etc. In this paper we present a 1-dimensional systolic architecture for the basic gray-scale morphology operations: dilation and erosion. Most other morphological operations like opening and closing, are also supported by the architecture since these operations are combinations of the basic ones. The advantages of our design stem from the fact that it has pipeline period = 1 (i.e., 100% processor utilization), it requires simple communications, and it is exploiting the simplicity of the morphological operations to make it possible to implement them in a linear target machine although the starting algorithm is a generalized 2-D convolution. We also propose a Locally Parallel Globally Sequential (LPGS) partitioning strategy for the best mapping of the algorithm onto the architecture. We conclude that for this particular problem LPGS is better than LSGP in a practical sense (pinout, memory requirement, etc.). Furthermore, we propose a chip design for the basic component of the array that will allow real-time video processing for 8- and 16-bit gray-level frames of size 512 × 512, using only 32 processors in parallel. The design is easily scalable so it can be custom-taylored to fit the requirement of each particular application.     

一种混合的四叉树分形图像编码

为克服四叉树分形编码中纹理信息丰富的图像块较难找到满足要求相似块的不足,在四叉树分形图像编码的基础上,提出了一种与BTC方法结合的混合分形编码方法。讨论了四叉树分形编码与BTC方法,综合了2种方法的优点,对四叉树分形编码中块尺寸为4×4且找不到满足要求相似块的图像块,采用BTC方法,并用标准图像进行仿真实验,给出了四叉树编码方法与本文方法的实验结果。实验结果表明:此方法能明显改善重构图像的MSE或PSNR指标。     

一种新的分形图像压缩编码方法

本文提出了一种将双线性内插与基于迭代函数系统的分形图像编码相结合的图像编码新方法。实验结果表明，与基本的自动分形图像编码方法相比，在基本保持重建图像质量的前提下，运算时间大大下降而压缩比有显著的提高。     

A Parallel ASIC Architecture for Efficient Fractal Image Coding

Fractal image coding is a compression technique with many promising features, but it has been primarily placed in the class of archival coding algorithms due to its computationally expensive encoding algorithm. Though fractal coding has been extensively optimized for speed, it is still not practical for real-time applications on most sequential machines. The problem with fractal coding lies in the large amount of pixel block comparisons that are required, which makes fractal coding better suited toward parallel systems. At the same time, VLSI area has become a much less important constraint in chip design due to better fabrication techniques and smaller micron technologies. This has lead to a recent trend for designing parallel subsystems and including multimedia ASIC circuitry on general purpose CPUs. In this paper, we will present a parallel ASIC array architecture for use in fractal encoding that performs a full domain quad-tree search in near real-time for standard sized gray scale images. The design is also scalable so that larger images can be encoded faster by adding chips to the array. In designing this architecture, we include novel optimizations at the algorithmic, architecture, and circuit levels.     

一种快速模糊矢量量化图像编码算法

本文在学习矢量量化和模糊矢量量化算法的基础上,设计了一种新的训练矢量超球体收缩方案和码书学习公式,提出了一种快速模糊矢量量化算法。该算法具有对初始码书选取信赖性小,不会陷入局部最小和运算最小的优点。实验表明,ＦＦＶＱ设计的图像码书性能与ＦＶＡ算法相比,训练时间大大缩短,峰值信噪比也有改善。     

一种改进的相关图像矢量量化编码算法

本文提出了一种改进的图像矢量量化编码算法。该算法通过采用增加预测块，以及根据相邻块状态进行控制信息的条件熵编码等改进方法，进一步提高了算法的编码效率，为了便于算法实现，本文对图像的边缘引进的一致的处理方法。测试结果表明，相对于无记忆适量量化编码算法，比特率约下降４０％，相对于文献［５］算法，比特率约下降１５％。     

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.