Scalable Compression and Transmission of Internet Multimedia

建议书#0104834TEXAS工程经验这个雄心勃勃的项目探索了具有挑战性的多媒体通信系统的算法设计和体系结构的几个新方向。对基于可伸缩信源编码的异类网络(例如，因特网)和噪声信道(例如，无线局域网)上的多媒体数据的传输采取统一的方法。该项目涉及的主题包括：1)基于变换系数位平面的高效算术编码的可扩展多媒体数据压缩。对于图像编码，像在新的JPEG-2000标准中一样使用了小波变换。重点是在传统的非渐进网格编码量化方案中引入渐进性。采用三维小波变换进行完全可伸缩的视频编码。将一种新的非均匀调制复重叠变换(NMCLT)应用于音频编码。为了实现高算术编码性能，在NMCLT或小波系数的高阶上下文建模上投入了大量的努力。此外，还研究了用于音频编码的NMCLT系数的量化噪声屏蔽和用于三维小波视频编码的运动信息挖掘的新方法。2)通过最优分包和联合拥塞与差错控制来实现因特网多媒体的可伸缩传输。研究了一种基于动态规划的可伸缩多媒体码流最优打包方案。还研究了次优但低复杂度的打包方案。拥塞控制被用来确定可用的传输速率，并设计了端到端的最优差错控制方案来减轻分组丢失的影响。这是通过在可伸缩信源编码和不等差错保护之间进行最佳权衡来实现的。

PROPOSAL #0104834TEXAS ENGINEERING EXP. STA.XIONG, ZIXIANGThis ambitious project explores several new directions in the algorithmic design and architecture of challenging multimedia communication systems. A unified approach is taken for transmission of multimedia data over heterogeneous networks (e.g., the Internet) and noisy channels (e.g., a wireless LAN) based on scalable source coding. Topics covered in the project are:1) Scalable multimedia data compression based on efficient arithmetic coding of bit planes of transform coefficients. For image coding, the wavelet transform is used like in the new JPEG-2000 standard. The focus is on introducing progressiveness in the traditionally non-progressive trellis coded quantization scheme. The 3-D wavelet transform is adopted for fully scalable video coding. A new nonuniform modulated complex lapped transform (NMCLT) is applied for audio coding. To achieve high arithmetic coding performance, a significant amount of effort is invested in high-order context modeling of the NMCLT or wavelet coefficients. In addition, new methods are studied for masking quantization noise of the NMCLT coefficients for audio coding and exploring the motion information for 3-D wavelet video coding.2) Scalable transmission of Internet multimedia via optimal packetization and joint congestion and error control. A dynamic programming based optimal packetization scheme for scalable multimedia bit streams isstudied. Suboptimal but low complexity packetization schemes are also investigated. Congestion control is used to determine the available transmission rate and an end-to-end optimal error control scheme devisedto mitigate the effects of pack loss. This is achieved by optimally trading off scalable source coding and unequal error protection.