CAREER: Multiresolution-Based Adaptive Image/Video Communications: An Integrated Approach

职业：基于多分辨率的自适应图像/视频通信：一种集成方法

• 批准号: 9703181
• 负责人: Kannan Ramchandran
• 金额: $ 21万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-07-01 至 2001-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9703181&HistoricalAwards=false
• 关键词: CAREER; Multiresolution; Based; Adaptive; Image

The implementation of the National Information Infrastructure initiative will require the efficient transmission and storage of voluminous amounts of multimedia traffic, particularly image and video data. This project offers a multidisciplinary attack on this challenging problem with the goal of providing a system-wide optimized solution rather than a possibly mismatched collection of efficient subsystem solutions. It advocates an integration, in both research and education, of relevant aspects of three engineering subfields that have been traditionally treated separately: Signal Processing, Communications, and Networks. The primary educational goals are to help develop interdisciplinary specialists, and to integrate research more heavily into engineering education. This project promotes an adaptive and integrated approach to the algorithmic design and architecture of next-generation visual communications systems for the compression and reliable delivery, over noisy time-varying channels and heterogeneous networks, of images and video. A unifying thread is the use of flexible multiresolution-based frameworks for 1) source coding, 2) channel coding and 3) joint source-channel coding, with the goal of maximizing the delivered image/video quality using fast algorithms. In education, the primary goals are to help develop multidisciplinary specialists, and to integrate research more heavily into both undergraduate and graduate education.

国家信息基础设施倡议的实施将需要高效传输和存储大量多媒体流量，特别是图像和视频数据。 该项目针对这一具有挑战性的问题提供了多学科的解决方案，其目标是提供系统范围内的优化解决方案，而不是可能不匹配的高效子系统解决方案集合。 它提倡在研究和教育方面整合传统上分别对待的三个工程子领域的相关方面：信号处理、通信和网络。 主要教育目标是帮助培养跨学科专家，并将研究更多地融入工程教育中。 该项目促进了下一代视觉通信系统的算法设计和架构的自适应和集成方法，用于在嘈杂的时变通道和异构网络上压缩和可靠地传输图像和视频。统一线程是使用灵活的基于多分辨率的框架进行 1) 源编码、2) 通道编码和 3) 联合源通道编码，目标是使用快速算法最大限度地提高所提供的图像/视频质量。 在教育方面，主要目标是帮助培养多学科专家，并将研究更多地融入本科生和研究生教育中。