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）可扩展编码器的严格分层结构代表了一个严重缺陷，对其实际部署构成了生存威胁，尽管随着异构网络和多样化设备功能的激增，对此类技术的需求日益迫切； ii）消除这一缺点需要从涉及公共信息的信息论原理出发，在最基本的层面上重新考虑问题。根本原因是，实际数据源实际上永远无法连续精炼——实现粗质量重建所需的信息不是更高质量重建所需信息的适当子集。因此，最优性需要将信息分为不同层公用的信息和每层“私有”的信息。研究工作分为几条：推导分层编码通用信息框架的理论基础、分析渐近和有限延迟性能增益、将理论见解转化为分层音频编码的实用框架、对具有记忆的源进行扩展，以及涉及采样分辨率、多通道音频和多视图视频的可扩展性。研究重点是消除可扩展多媒体编码器次优的根本原因。这种限制的后果体现在行业的业务决策中，即避免现有的可扩展编码器，并默认采用各种质量级别的冗余、独立编码的浪费（存储和网络资源）替代方案。因此，除了对信息论的根本贡献之外，成功消除这一缺点将显着影响多媒体存储和网络的效率，从而影响更广泛的相关高科技行业，包括多媒体内容交付、无线通信以及满足多媒体存储和网络需求的关键努力。对网络资源的需求迅速增长。