压缩域图像／视频信息处理技术的研究

新世纪多媒体应用和业务的构建面临着新的挑战,而传统的压缩和处理相互分离的模式无法满足要求。为此,将进行基于压缩域的视频／图像信息分析、处理与检索技术的研究,提供一种压缩和处理相结合的信息处理模式。其研究成果能够极大地提高构筑于通信网络上的信息业务和应用系统的整体性能,给我国信息产业的发展带来良好的经济效益。     

面向产业链云服务平台的分布式备件库存协同控制方法与软件工具研究

针对制造业产业链协同服务平台的备件业务协作需求,提出跨节点的库存协同解决方案并建立近期需求预测计算模型。结合分布式节点企业的历史交易数据、库存数据的实时采集与处理应用,保障库存控制方案的实效性。采用MapReduce框架对模型参数计算过程进行优化,提高运算速度。基于遗传算法获取模型计算最优解,并将模型计算结果推送至下游经销商企业群,由反馈信息控制订单的动态生成。并将该模式应用在汽车产业链云服务平台,压缩了产业链响应时间。     

基于轻量化模型的智能配电站房云边协同应用模式研究

为了解决电力行业图像智能识别由于云端集中推理模式带来的网络带宽限制和数据传输时延方面的问题,在云边协同应用与人工智能深度学习网络模型轻量化压缩两个方向上进行探索研究和融合应用,通过云边协同架构体系和主流人工智能深度学习网络模型压缩方法进行对比分析,提出了一种基于参数量化模型压缩的云边协同应用模式,并在实际运行中的智能配电站房中进行现场测试,通过业务应用测试和数据结论验证了该应用模式的可行性,通过该云边协同应用模式实现了云端模型复用,减少了额外开发边端模型的人力物力投入,具有较高的示范和推广价值。     

三网融合下手机云计算的应用模式探讨

云计算作为一种新兴的信息计算模型,为网络运营商提供了低成本的海量信息处理及存储服务,同时也为三网融合平台云化架构的底层支撑奠定了基础。从当前亿级大规模智能手机应用平台已经面临计算和存储的瓶颈问题出发,将云计算服务应用于手机通信和数据处理业务中,探讨了云计算在手机平台中的应用模式,并从远程控制、数据同步、定位跟踪以及资源推送等方面进行论述,此模式能够有效提升手机业务能力和降低运营成本。     

利用地面公网实现战术数据链远程通信研究

利用地面公共网络使地理位置远离的多个数据链系统无缝互连,可以支持和提高相对独立的多个战术数据信息链实现超视距的互操作测试和训练。文章分析了两种地面网络通信模式：虚拟专用局域网业务模式和应用层网关模式。比较两种模式应用特点,发现虚拟专用局域网业务模式可以将多个数据链网络连接成一个虚拟局域网,传输数据方便,但是应用层网关更加适合数据链接口的要求并且可以对传输数据进行处理和报文格式修改。     

面向协同设计系统的分布式群决策支持技术研究

在探讨业务处理中间件的分布计算模式、多主体控制以及分布式问题处理多库管理技术基础上,该文重点分析群体决策支持的协问设计系统分布计算环境;提出并实现了领域问题求解策略、应用模块的模型化管理方法以及分布式问题求解及其过程监控.同时深入研究协同设计系统业务处理中间件的信息资源共享和分布式问题求解的多维信息交互过程,实现了协同设计系统开放式群体决策集成开发平台.最后以预研项目为研究背景,实现了设备设计的产品集成化开发设计,取得了明显的实际应用效果.     

神经网络在彩色图像压缩中的应用

文中旨在提出一种基于神经网络的图像压缩算法对彩色图像信息进行处理,从而减少大规模彩色图像的冗余度,方便其传输、存储及加密等。该算法通过将BP（Back Propagation）神经网络用于彩色图像压缩,利用其多层前馈网络的模式变化能力,实现了对由RGB编码得到的彩色图像数字矩阵进行的压缩编码。经Matlab仿真实验表明,该算法具有良好的压缩效果,且与灰度编码下的图像压缩结果对比,具有更好的压缩效率及保真效果,并能有效地保留原彩色图像的色彩信息,能够满足彩色图像压缩处理的要求。     

利盟金融行业解决方案

金融行业电子化的发展,使得金融机构的业务从纯粹的手工操作逐步实现了业务处理的电子化。各种原始单据上的部分信息被输入到计算机中,成为数字化的信息进行传递和处理,业务处理的效率和能力大为提高。然而,大量的金融应用系统的处理都是基于手工输入数据信息的处理,由于手工输入、数据传递过程中可能出现的差错以及信息的不完整性     

探索构建远程办公信息安全技术

阐述的远程办公指的是网络用户不受地域限制,穿越互联网对业务进行实时安全处理的工作模式,是计算机网络技术的一种高级应用.在数据信息穿越互联网传递给远程用户时,如何保证数据信息的机密性,完整性和不可否认性,是数据信息安全的关键技术问题.     

实时遥测数据信源压缩技术

遥测是卫星、飞船和运载火箭等航天器系统的关键功能之一。随着航天器功能、性能的提高和系统规模、技术复杂性的增大,对遥测的要求在不断提高;由于航天器功耗、重量、天地通信带宽或中继业务费用等约束限制,传统PCM遥测技术和分包遥测技术难以满足当前要求;在分析遥测数据信息冗余度的基础上,提出一种实时在线遥测信源压缩方案,以高性能数据处理计算机为核心完成信源数据搜集和组帧,然后在时间和空间维度进行压缩编码,最后按照兼容CCSDS分包遥测的标准进行分段处理、信道编码和遥测下行,该方案兼容CCSDS技术标准,信道利用效率高、压缩后的信息冗余度低,应用构建费用低、接口简单和可扩充性好。     

压缩域多媒体数据处理技术研究

多媒体数据压缩技术是多媒体、网络通讯以及计算机等应用领域的一项关键技术。多媒体数据经过压缩后再进行存储或通过网络进行传输,这已经逐渐成为多媒体应用中的标准模式;同时,多媒体应用中所涉及到的各种媒体数据,如图象、视频和音频数据,往往需要进行各种灵活的操作与处理,因此,压缩域多媒体数据直接处理技术成为一项很有意义的研究领域。文中首先就压缩数据处理的基本概念进行讨论,然后集中分析了这一研究领域的重要研究     

DCT域图象处理和特征提取技术

现今 ,大量的图象与视频信息都是以压缩数据格式进行存储和传输的 .DCT(Discrete Cosine Transform离散余弦变换 )是目前应用最为广泛的多媒体数据压缩技术之一 .直接在 DCT域实现如视频编辑、特征提取等传统空域处理技术 ,能够避免繁琐的压缩数据编、解码操作 ,减少处理时间和数据处理量 ,节省内存空间 .这一技术对于高速海量的数据处理场合 ,如 Internet信息检索、视频编辑和检索、远程监视图象的理解等 ,是很有吸引力的 ,因此其是近年来国际上有关领域的研究热点之一 .本文对近年来文献中所见的 DCT域图象处理和特征提取技术进行了回顾和综述 ,并在此基础上对其发展方向进行了探讨     

基于压缩域的图像检索技术

图像检索技术是多媒体应用中的关键技术，现有的基于内容图像检索技术大都是基于非压缩域的，对于目前普遍存在的压缩格式图像，采用这种技术必须先解压再检索，不但计算量大，而且需占用较多的中介存储空间，所以严重影响了检索系统的实时性和灵活性，同时各种压缩标准(如JPEG，MPEG，JPEG2000等)的推出与普及也促使人们寻求可以直接在压缩域操作的检索技术，该文对现有的压缩域图像检索技术的发展进行综述，并讨论了未来可能的研究方向。     

多算法融合比较的图像文件索引压缩

近年来由于科技的发展和互联网的兴起,图像资料已被广泛地应用在网络上,而图像压缩不但可以节省图像资料占用的内存空间,并且可以加速其传输速度,因此图像压缩技术目前被广泛应用于医学、手机、数据传输、多媒体影音、互联网络等。这里主要是针对无失真的图像压缩技术,先将原始图像转成256色的GIF格式,然后再建立一个索引矩阵,矩阵中元素是由原色RGB信息对应所组成,利用索引矩阵排序法并配合编码簿,再加上配合LZW、CALIC、JPEG2000、JPEG-LS等不同压缩算法,来比较压缩的效果。     

Data compression in multimedia computing — principles and techniques

Integrated multimedia systems process text, graphics, and other discrete media as well as digital audio, and video data. Considerable amounts of graphics, audio and video data in their uncompressed form, especially moving pictures, require storage and digital network capacities that will not be available in the near future. Nevertheless, local, as well as networked, multimedia applications and systems have become realities. In order to cope with these storage and communication requirements in such integrated multimedia systems, compression technology is essential. This papers starts with a brief motivation of the need for compression and subsequently states the essential requirements for these techniques in the scope of multimedia systems and applications. As most of these techniques apply the same principles, namely, the source, entropy, and hybrid coding fundamentals, these are explained in detail. Based on a general framework of the steps encountered in a compression system — data preparation, processing, quantization, and entropy coding — this paper outlines details about the techniques developed by CCITT (H.261, i.e., px64), in the ISO/IEC (JPEG, MPEG) standardization bodies and the proprietary DVI system.     

Intelligent multimedia data: data + indices + inference

In this paper, we present a novel approach for multimedia data indexing and retrieval that is machine independent and highly flexible for sharing multimedia data across applications. Traditional multimedia data indexing and retrieval problems have been attacked using the central data server as the main focus, and most of the indexing and query-processing for retrieval are highly application dependent. This precludes the use of created indices and query processing mechanisms for multimedia data which, in general, have a wide variety of uses across applications. The approach proposed in this paper addresses three issues: 1. multimedia data indexing; 2. inference or query processing; and 3. combining indices and inference or query mechanism with the data to facilitate machine independence in retrieval and query processing. We emphasize the third issue, as typically multimedia data are huge in size and requires intra-data indexing. We describe how the proposed approach addresses various problems faced by the application developers in indexing and retrieval of multimedia data. Finally, we present two applications developed based on the proposed approach: video indexing; and video content authorization for presentation.     

MPEG Video Encryption Algorithms

Multimedia data security is important for multimedia commerce. Previous cryptography studies have focused on text data. The encryption algorithms developed to secure text data may not be suitable to multimedia applications because of the large data size and real time constraint. For multimedia applications, light weight encryption algorithms are attractive.We present four fast MPEG video encryption algorithms. These algorithms use a secret key to randomly change the sign bits of Discrete Cosine Transform (DCT) coefficients and/or the sign bits of motion vectors. The encryption is accomplished by the inverse DCT (IDCT) during the MPEG video decompression processing. These algorithms add a small overhead to MPEG codec. Software implementations are fast enough to meet the real time requirement of MPEG video applications. The experimental results show that these algorithms achieve satisfactory results. They can be used to secure video-on-demand, video conferencing, and video email applications.     

图象和视频的检索技术

随着网络技术的发展,多媒体数据将成为网络服务的主要内容,因此对多媒体数据管理问题的研究成为近几年的热点。由于媒体信息表现性质的不同,传统关系数据库的检索方式不再适用于图象和视频,因此,必须采用基于自身内容的检索方式。文章对基于内容的图象和视频检索技术分不同层次进行了全面的总结,内容包括依据基本特征,色彩、纹理、形状、和位置关系的技术,视频的场景分割、关键帧提取技术以及基于声音、文字的检索技术等,并阐述了各种方法的优缺点,现状及发展方向。     

Towards a framework for large-scale multimedia data storage and processing on Hadoop platform

Cloud computing techniques take the form of distributed computing by utilizing multiple computers to execute computing simultaneously on the service side. To process the increasing quantity of multimedia data, numerous large-scale multimedia data storage computing techniques in the cloud computing have been developed. Of all the techniques, Hadoop plays a key role in the cloud computing. Hadoop, a computing cluster formed by low-priced hardware, can conduct the parallel computing of petabytes of multimedia data. Hadoop features high-reliability, high-efficiency, and high-scalability. The numerous large-scale multimedia data computing techniques include not only the key core techniques, Hadoop and MapReduce, but also the data collection techniques, such as File Transfer Protocol and Flume. In addition, distributed system configuration allocation, automatic installation, and monitoring platform building and management techniques are all included. As a result, only with the integration of all the techniques, a reliable large-scale multimedia data platform can be offered. In this paper, we introduce how cloud computing can make a breakthrough by proposing a multimedia social network dataset on Hadoop platform and implementing a prototype version. Detailed specifications and design issues are discussed as well. An important finding of this article is that we can save more time if we conduct the multimedia social networking analysis using Cloud Hadoop Platform rather than using a single computer. The advantages of cloud computing over the traditional data processing practices are fully demonstrated in this article. The applicable framework designs and the tools available for the large-scale data processing are also proposed. We show the experimental multimedia data including data sizes and processing time.     

Reconfigurable media processing

Multimedia processing is becoming increasingly important with wide variety of applications ranging from multimedia cell phones to high definition interactive television. Media processing techniques typically involve the capture, storage, manipulation and transmission of multimedia objects such as text, handwritten data, audio objects, still images, 2D/3D graphics, animation and full-motion video. A number of implementation strategies have been proposed for processing multimedia data. These approaches can be broadly classified into two major categories, namely (i) general purpose processors with programmable media processing capabilities, and (ii) dedicated implementations (ASICs). We have performed a detailed complexity analysis of the recent multimedia standard (MPEG-4) which has shown the potential for reconfigurable computing, that adapts the underlying hardware dynamically in response to changes in the input data or processing environment. We therefore propose a methodology for designing a reconfigurable media processor. This involves hardware–software co-design implemented in the form of a parser, profiler, recurring pattern analyzer, spatial and temporal partitioner. The proposed methodology enables efficient partitioning of resources for complex and time critical multimedia applications.