基于ADV212的实时图像压缩系统

采用专用图像压缩芯片ADV212设计了一个能对分辨力高、数据量大的图像进行实时压缩的系统.该系统能够根据输入数据率自适应调整压缩比,实时产生JPEG2000格式的码流.ADV212输出的码流经过加密后可以实时输出也可在本系统内存储.实验结果表明,该系统能满足实时性要求,同时所得重建图像具有较好的主观视觉感受和较高的峰值信噪比.     

码流分配决策的VHDL实现及仿真

为解决图像码流庞大带来的存储和传输困难,提出了一种针对多路图像译码的码流分配决策,并采用VHDL语言来实现。码流分配前,对图像头文件进行检测,采用两片外挂RAM对检测后的码流进行乒乓操作后,送入多路并行图像处理模块,处理后的码流采用同样的分配方式进行缓存。结果表明该决策真正实现了图像码流传输的实时性和准确性,而且其可移植性强,可以应用到图像处理的很多领域,成为提高码流缓存和传输速度的桥梁。     

基于降斑处理的SAR图像实时压缩系统

为了对SAR图像进行实时压缩和本地存储,基于FPGA和ADV212芯片,利用空域增强Lee滤波算法,设计实现了SAR图像实时降斑压缩系统。测试结果表明,在降斑处理基础上,系统能对大数据量SAR图像进行压缩,产生JPEG2000格式码流,满足实时性、压缩模式和压缩比可选的要求,可支撑目标探测、区域监控等任务应用。     

实时目标检测与跟踪系统的设计与实现

针对固定监控场景设计并实现了一个实时的运动目标检测与跟踪系统.在复杂背景下,改进的三帧差分法能准确、快速检测出运动目标.金字塔图像的Lucas Kanade光流法跟踪目标容易丢失;传统的模板匹配跟踪方法由于对图像利用率高,其跟踪比较准确,但计算量大.文章将两者结合起来,可以避免上述问题.实验表明,该算法能较好地实现目标跟踪、获得目标运动轨迹,且具有良好的实时性和鲁棒性.     

一种天文光电图像序列弱小目标实时检测算法

地基大视场天文光电观测系统获取的序列图像中,空间目标和数目众多的恒星目标成像特性相似,大部分都表现为弱、小目标特性,实现它们稳健实时检测具有较大的难度.本文在深入分析天文光电图像弱小目标成像特点的基础上,结合实际工程对目标检测的强实时性和高检测概率需求,针对恒星目标和空间目标的时空域特性差异,提出了一种基于时空域联合滤波的弱小目标枪测算法,首先在空域上通过抑制背景增强目标,然后在时域上分别通过多帧相关运算和多帧差分运算,快速有效地检测恒星目标和空间目标.最后结合实测数据和硬件平台,验证了该方法的有效性及实时性.     

基于跟踪微分器的波门跟踪算法的研究

针对目标自动跟踪系统对目标跟踪算法实时性和精确性要求高的特点,提出了一种基于跟踪微分滤波器的运动目标跟踪方法.该算法利用跟踪微分器预测目标中心在下一帧体现在图像中可能出现的位置,以该位置为波门目标检测的中心,减少了目标的搜索范围,缩短了算法的运算时间.仿真结果表明,该方法具有不依赖于目标运动模型,实时性好,精确性高等优...     

基于FPGA图像分块解码的系统设计

讨论了一种硬件实现卫星图像高速解码的系统设计方案。采用图像分块解码的方式,使用现场可编程门阵列（FPGA,Field Programmable Gate Array）的IP核实现片内缓存,减少了外挂RAM,降低了设计的复杂度。利用异步FIFO可以同时读写的特性,实现了码流检测与解码同时进行,并通过多路并行和流水线操作对图像码流进行高速解码。整个设计采用VHDL对算法完成建模和实现,仿真和综合结果表明该方案占用的硬件资源少,解码速度快,实现了图像码流解码的实时性和准确性,而且可移植性强,可以应用到图像处理的很多领域。     

基于多DSP的H．264高清视频实时编码系统

最新H．264国际视频压缩标准为达到高效率的压缩性能而采用了复杂的算法,使得采用该标准实现高清视频编码压缩变得异常困难。参考相关论文,给出一种基于多条带、多DSP的并行编码系统。该系统按照DSP的数目及各DSP的处理能力,将当前高清视频图像横向上分割为大小不一的若干子图像并分别送各DSP进行并行编码压缩,最终合并各DSP生成的子码流,输出整帧图像编码压缩码流。测试结果显示,该系统对1920×1080P高清视频图像,在2～8Mb／s的码率下,可以达到每秒25帧以上的实时编码压缩。     

天文光电观测系统实时信息处理机的设计与实现

针对地基天文光电观测系统获取图像数据量大、实时处理难度高等特点,设计并实现了以高可靠CPCI工控机为平台、基于FPGA+双DSP TMS320C6455的实时信息处理机。详细介绍了实时信息处理机硬件结构,深入分析了实时信息处理机的设计特点。针对实时信息处理机实时图像获取和实时图像处理的主要任务,重点描述了工程实现过程中图像获取及处理流程、弱小目标检测算法实现、DSP任务分割和速度优化等。外场实验及大量实测数据处理结果验证了该处理机的实时性和处理能力,满足了天文光电观测系统的要求,为高分辨率图像的处理运算提供了可靠的硬件平台。     

一种小目标快速识别与跟踪方法

提出了一种基于多帧相关技术与波门选通技术相结合的快速目标识别与跟踪方法.利用多级滤波抑制噪声的方法对单帧采集图像进行处理,得到潜在的目标信息,然后利用多帧相关性和目标的运动连续性确定目标;对于后续图像引入波门选通技术,在波门内进行预处理、分割与识别跟踪.探讨了多帧相关技术中目标确定的理论判据,综合考虑目标的尺寸因素和目标的运动特征,提出一种新的波门设定方法.实验结果表明,对于信噪比(SNR)大于等于2.0的图像,该方法能够在获得目标的运动参数及运行轨迹的基础上显著地提高识别效率,实现对运动目标的实时分析,同时更好地抑制背景噪声.     

高性能三维小波视频编码方法

讨论并实现了基于３Ｄ－ＳＰＩＨＴ算法的三维小波视频编码方法。该方法建立在真三维小波分解基础上，通过定义一种新的时空方向树结构，实现了静止图像ＳＰＩＨＴ算法的三维扩展。该方法不涉及运动估计，具有较低的计算负荷和时间延迟，所产生的视频流是完全嵌入的。实验结果表明该方法能够快速地、高质量地压缩视频图像，是一种很有潜力的视频编码方法。     

运动估计技术在图像匹配中的应用

在运动估计技术的基础上提出了一个巡航导弹制导系统中图像匹配问题的解决方案，及其具体实现。实验证明这种硬件电路能够实时实现灰度 匹配。     

Optical computing techniques for image/video compression

The advantage of optics is its capability of providing highly parallel operations in a three-dimensional space. In this paper, we propose optical architectures to execute various image compression techniques. We optically implement the following compression techniques: transform coding, vector quantization, video coding. We show many generally used transform coding methods, for example, the cosine transform, can be implemented by a simple optical system. The transform coding can be carried out in constant time. Most of this paper is concerned with an innovative optical system for vector quantization using holographic associative matching. Limitations of conventional vector quantization schemes are caused by a large number of sequential searches through a large vector space. Holographic associative matching provided by multiple exposure holograms can offer advantageous techniques for vector-quantization-based compression schemes. Photorefractive crystals, which provide high-density recording in real time, are used as our holographic media. The reconstruction alphabet can be dynamically constructed through training or stored in the photorefractive crystal in advance. Encoding a new vector can be carried out by holographic associative matching in constant time. An extension to interframe coding using optical block matching methods is also discussed     

一种高效的运动补偿三维小波视频编码方案

该文提出了一种高效的运动补偿三维小波视频编码方案。该方案采用运动补偿时域分析技术,以有效去除视频序列中存在的时间冗余。然后,基于视频序列的运动特征,自适应确定帧组结构,在提高编码效率的同时降低内存需求和运算复杂度。最后,根据小波图像系数特性,采用基于四叉树分裂的小波图像编码方法对三维时/空子带进行编码,以获得更高的压缩效率。实验结果表明,与其它运动补偿三维小波视频编码方法相比,该文提出的编码方案能够获得更好的性能。     

Image/video communications: joint source/channel coding

Transmission of image/video messages over communication networks is becoming a standard way of communication due to very efficient compression algorithms that reduce required channel capacity to an acceptable level. However, all compression standard techniques are strongly sensitivitive to channel disturbances and their application is suitable only for practically noiseless channels. In standard noisy channels, the effect of errors on a compressed data bit stream can be divided into two categories: systematic errors defined by the structure of data blocks, and random errors caused by amplitude changes of transmitted components. A systematic error can be detected at the receiver through control of the data stream structure and corrected by error concealment methods or by automatic repeat request (ARQ) procedures. Random errors, noise and burst‐like errors, as well as impulse noise, should be controlled through channel coding. It is reasonable that an integrated source and channel coding methods should be preferred and should give better coding performance. In this paper, a new framework for an image/video coding approach has been presented in which the source and channel coding is integrated in a unique procedure. Image compression is performed in a standard way of the JPEG algorithm based on discrete cosine transform (DCT) and error control coding is based on the real/complex‐number (N,M) BCH code using discrete Fourier transform (DFT) specified with zeros in the time domain, i.e. with roots in the frequency domain. Efficiency of the proposed method is tested on two examples, an one‐dimensional real‐valued time sequence coded by real‐number (20,16) BCH code using DFT, and an example of an image coded by complex (10,8) BCH code using DFT with the correction ability of up to 8 impulses per transmitted 8×8 block. In addition, two decoding methods based on Berlekamp–Massey algorithm (BMA) and the minimum‐norm algorithm (MNA) have also compared. Copyright © 1999 John Wiley & Sons, Ltd.     

Low calculation cost of HEVC coding unit size based on spatial homogeneity detection

For the same video quality, HEVC gives 25% to 50% bitrate savings, compared to its predecessor the Advanced Video Coding H.264 and thus supports resolutions up to 8 K UHD. However, the reduction in bitrates provided by the HEVC leads to an increase in the computational cost of the encoding operation. This complexity can become a true handicap especially for real-time video streaming and also for VANET (Vehicular Ad-Hoc Network) applications such as traffic safety and Video surveillance. The improvement in the bitrates and also the increase in the calculation cost are due to the use of large and multi-sized coding, prediction and transform blocks. Indeed, the H264 coder is based on structure macroblocks with sizes 4 × 4, 8 × 8 and 16 × 16, while H.265 depends on Coding Tree Units (CTUs), CTUs select sizes 4 × 4, 8 × 8, 16 × 16, 32 × 32 and 64 × 64 blocks. This paper proposes a fast CU (Coding Unit) size decision method to reduce the HEVC calculation cost based on spatial homogeneity. Compared with the HM16.13 benchmark test model, the average coding time is reduced by around 40% for CIF / QCIF video sequences, 35% to 43% for class A, B and C test sequences. These important reductions in coding time are obtained with negligible loss of quality and an average increase in bitrates which does not exceed 0.89% for the three configuration modes (All intra, Random Access and Low Delay).     

Digital video coding standards and their role in videocommunications

The efficient digital representation of image and video signals has been subject of considerable research over the past 20 years. With the growing availability of digital transmission links, progress in signal processing, VLSI technology and image compression research, visual communications has become more feasible than ever. Digital video coding technology has developed into a mature field and a diversity of products has been developed-targeted for a wide range of emerging applications, such as video on demand, digital TV/HDTV broadcasting, and multimedia image/video database services. With the increased commercial interest in video communications the need for international image and video coding standards arose. Standardization of video coding algorithms holds the promise of large markets for video communication equipment. Interoperability of implementations from different vendors enables the consumer to access video from a wider range of services and VLSI implementations of coding algorithms conforming to international standards can be manufactured at considerably reduced costs. The purpose of this paper is to provide an overview of today's image and video coding standards and their role in video communications. The different coding algorithms developed for each standard are reviewed and the commonalities between the standards are discussed     

DSP图像处理技术在板带纠偏系统中的应用

运用DSP图像处理的解决办法,设计了一套基于DSP数字图像处理技术的板带纠偏电视检测可视化系统.DSP计算速度快、可并行处理,成功解决了视频检测数据处理量大、系统实时性要求高之间的矛盾.设计中所选取的TMS320DM642芯片作为一款专用的数字多媒体处理芯片,具有丰富的外围接口和特色的视频图像采集功能,这就使该图像处理模块集成了图像的采集回放与图像处理的功能,摒弃了单独的图像采集卡,避免了数据传输过程中所出现的问题.在深入研究DSP系统的基础上,制定了系统实现的方法并在实验室条件下实现了板带纠偏与视频检测,检验结果完全能够满足实时性和精度要求.     

基于CUDA平台的并行化实时视频编码

HD视频的编码技术具有广阔的应用前景,为解决其大数据量实时处理的瓶颈问题,提出一种基于CUDA平台的并行编码系统架构。根据CUDA平台软硬件结构特性,采用三级并行机制;并提出一种高并行化快速ME搜索算法;同时合理分配内存空间,实现大数据量的实时运算与存取。实验结果表明,方案具有高并行度,高编码速率的特点,对HD视频可达到实时编码要求。     

一种基于监控系统的图像清晰度检测算法

视频图像的清晰度是衡量视频监控系统的重要指标。通过比较灰度变化函数、频谱函数、方差梯度函数、灰度熵函数评价图像清晰度的优劣,提出了一种新的清晰度评价函数。通过测试大量的图片和监控视频,对改进后的算法和其他检测算法的性能进行了比较,结果表明,提出的检测算法具有单峰性强、灵敏度高、无偏好性、信噪比高等特点,能够自动实时有效地完成对视频图像清晰度的检测。