CIF: Small: The Common Information Framework and Optimal Coding for Layered Storage and Transmission of Audio Signals

CIF：Small：音频信号分层存储和传输的通用信息框架和最佳编码

• 批准号: 1320599
• 负责人: Kenneth Rose
• 金额: $ 49.48万
• 依托单位: University of California-Santa Barbara
• 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: 2013-10-01 至 2016-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1320599&HistoricalAwards=false
• 关键词: CIF; Small; Common; Information; Framework

The premise of this research project is: i) the rigid hierarchical structure of scalable coders represents a critical flaw that poses an existential threat to their practical deployment, despite compelling demand for such technology with the proliferation of heterogeneous networks and diverse device capabilities; ii) eliminating this shortcoming requires reconsideration of the problem at its most fundamental level, from information theoretic principles involving common information. The root cause is that real data sources are virtually never successively refinable -- the information required to achieve coarse quality reconstruction is not a proper subset of the information required for higher quality reconstruction. Hence, optimality necessitates splitting the information into what is common to different layers, and what is "private" to each layer. Research is pursued along several lines: derivation of a theoretical foundation for a common information framework for layered coding, analysis of asymptotic and finite delay performance gains, translation of theoretical insights into a practical framework of layered audio coding, extensions to sources with memory, and to scalability involving sampling resolution, multi-channel audio, and multi-view video.The research focus is on eliminating the underlying cause for suboptimality of scalable multimedia coders. Ramifications of this limitation are exemplified by the industry's business decision to avoid existing scalable coders and default to the wasteful (in storage and network resources) alternative of redundant, independent encoding at various quality levels. Thus, beside fundamental contributions to information theory, successful elimination of this shortcoming would significantly impact the efficacy of multimedia storage and networking, and thereby the broader sector of related high-tech industries including multimedia content delivery, wireless communications, and the critical effort to satisfy the rapidly growing demand for network resources.

该研究项目的前提是：i）可伸缩编码器的严格的分层结构代表了对其实际部署构成存在威胁的关键缺陷，尽管随着异构网络和多样化设备能力的激增，对这种技术的需求迫切; ㈡消除这一缺陷需要从最根本的层面重新考虑问题，从涉及公共信息的信息论原理出发。根本原因在于，真实的数据源实际上从来不是连续可细化的--实现粗质量重建所需的信息不是更高质量重建所需的信息的真子集。因此，最优性需要将信息分为不同层的公共信息和每层的“私有”信息。研究工作沿着几条路线进行：用于分层编码的公共信息框架的理论基础的推导，渐近和有限延迟性能增益的分析，将理论见解转化为分层音频编码的实际框架，对具有存储器的源的扩展，以及对涉及采样分辨率的可缩放性的扩展，多声道音频，研究的重点是消除可伸缩多媒体编码器次优的根本原因。这种限制的分支由行业的商业决策例示，以避免现有的可扩展编码器，并默认为在各种质量级别的冗余独立编码的浪费（在存储和网络资源中）的替代方案。因此，除了对信息理论的基本贡献之外，成功消除这一缺点将显著影响多媒体存储和网络的效率，从而影响相关高科技行业的更广泛领域，包括多媒体内容交付，无线通信，以及满足快速增长的网络资源需求的关键努力。