Architectures for Lossy Compression: A Fundamental Study

信息源（声音、图像和视频）本质上是模拟的：它们可以用实数表示。另一方面，当今信息时代的通用货币是数字货币：一串抽象的比特。模数分离架构是当今主要的操作模式，主要是由于其模块化和可扩展性。虽然仍然没有采用联合源信道编码，但有损压缩可以通过“模拟标记”数字压缩信息源（例如：最高有效位和最低有效位）来帮助。在本项目中，采用有损压缩的基本观点来深入了解适合不同网络配置的架构。本研究的一个重要组成部分是关注模拟信息源的简单统计知识。在重建方面，特别令人感兴趣的是二次保真度准则。该项目的目标是：(a)了解模拟-数字分离架构最优的制度；(b)识别适当的模拟标签以数码形式表示，以便在网络上通讯时得到最佳利用；(c)确定这种新架构比传统的模拟-数字分离架构产生显著改进的场景。首席研究员在解决分布式压缩和多重描述中长达数十年的开放问题方面的最新进展被用作研究议程的起点。

Information sources (voice, images and video) are analog in nature: they can be represented by real numbers. On the other hand, the common currency of today's information age is digital: an abstract sequence of bits. The analog-digital separation architecture is the dominant mode of operation today, due primarily to its modularity and scalability. While still not employing joint source-channel coding, lossy compression might be helped by ``analog-tagging'' the digitally compressed information sources (example: most and least significant bits).In this project, a fundamental view of lossy compression to shed insight into what architectures are appropriate for different network configurations is taken. An important component of this study is the focus on simple statistical knowledge of the analog information source. On the reconstruction side, of particular interest is the quadratic fidelity criterion. The goals of this project are: (a) to understand regimes where the analog-digital separation architecture is optimal; (b) to identify the appropriate analog tags to digital representation that can be best utilized when it comes to communicating over a network; (c) identify scenarios where such new architectures yield significant improvement over the conventional analog-digital separation architecture. Recent progress by the principal investigator in resolving decades-long open problems in distributed compression and multiple description is used as the starting point for the research agenda.