CIF: Small: Sampling Rate Distortion

CIF：小：采样率失真

• 批准号: 1319799
• 负责人: Prakash Narayan
• 金额: $ 49.97万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1319799&HistoricalAwards=false
• 关键词: CIF; Small; Sampling; Rate; Distortion

This research takes an information theoretic approach to understanding principles that govern a coordinated rate-efficient sampling of multiple signals and centralized compression of the sampled subset. The goal is to reconstruct the entirety of the signals within acceptable distortion levels. The research has three main components: an integrated analysis of sampling and rate distortion behavior, and their tradeoffs; sampling rate distortion theory for Markov random fields; and sampling rate distortion performance for signals with memory. Expected outcomes are a characterization of fundamental performance limits of optimum sampling rate and lossy compression rate and their interplay, together with the best choice of sampling mechanisms and attendant processing for reconstruction.The investigators' technical approach involves the development of a principle of "sampling rate distortion" which lies at the intersection of specialities in information theory and signal processing, and has the larger objective of elucidating material connections between sampling and rate distortion performance. The performance of specific sampling and rate distortion processing schemes will be investigated. Specific groups of open problems chosen for investigation address a general class of multisignal models for sampling and lossy data compression. These are motivated by potential applications including dynamic thermal management for on-chip temperature control during runtime; network function computation; and image restoration, surface reconstruction and visual integration in computer vision.

这项研究采用信息论方法来理解控制多个信号的协调高效采样和采样子集的集中压缩的原理。目标是在可接受的失真水平内重建整个信号。该研究由三个主要部分组成：采样和率失真行为及其权衡的综合分析；马尔可夫随机场的采样率失真理论；以及带记忆信号的采样率失真性能。预期结果是最佳采样率和有损压缩率的基本性能限制及其相互作用的表征，以及采样机制的最佳选择和重建的伴随处理。研究人员的技术方法涉及开发“采样率”原则失真”，它位于信息论和信号处理专业的交叉点，其更大的目标是阐明采样和速率失真性能之间的物质联系。将研究特定采样和率失真处理方案的性能。选择用于研究的特定开放问题组解决了用于采样和有损数据压缩的通用多信号模型。这些都是由潜在的应用推动的，包括运行时片上温度控制的动态热管理；网络函数计算；以及计算机视觉中的图像恢复、表面重建和视觉集成。