Algorithms for optimal design of multiple description source codes

现代通信技术的出现对多媒体传输提出了新的挑战。在有线和无线网络中遇到的这些挑战之一是必须减轻分组丢失的影响。有效解决这个问题的范例是多描述编码（MDC）。MDC的基本思想是创建信号的几个描述，以便可以从每个单独的描述中重建源到一定的保真度，并且当有更多描述可用时，它们可以彼此细化，从而导致更高保真度的重建。所提出的研究的主要目标是开发有效的算法设计的最佳多描述源代码。重点将放在两种方法的MDC：多描述标量量化和不均匀擦除保护可伸缩码流的打包。除了为先前制定的优化问题开发新的解决方案（更快和/或更高精度）之外，申请人还将对现有框架提出创新，以提供更高性能的承诺。该研究将为在有损网络上进行鲁棒多媒体传输提供新的技术，从而更有效地利用传输速率中的可用资源。这些技术将直接应用于实践。此外，这项研究将带来新的见解，在该地区的最佳MDC设计，从而有助于知识和理解在该地区的进步和奠定背景，为进一步的研究。

The advent of modern communications raises new challenges for multimedia transmission. One of these challenges, encountered in both wired and wireless networks, is the necessity to alleviate the impact of packet loss. A paradigm to effectively solve this problem is multiple description coding (MDC). The basic idea in MDC is to create several descriptions of the signal such that the source can be reconstructed to a certain fidelity from each individual description, and when more descriptions are available, they can refine each other, leading to a higher fidelity reconstruction. The main objective of the proposed research is the development of efficient algorithms for the design of optimal multiple description source codes. The emphasis will be on two approaches for MDC: multiple description scalar quantization and uneven erasure protected packetization of scalable codestreams. Beside developing new solutions (faster and/or of higher accuracy) to previously formulated optimization problems, the applicant will propose innovations to the existing frameworks that offer the promise of higher performance. The proposed research will lead to new techniques for robust multimedia transmission over lossy networks, which more efficiently use the available resources in transmission rate. These techniques will be directly applicable in practice. Additionally, this research will bring new insights in the area of optimal MDC design, thus contributing to the advancement of knowledge and understanding in the area and laying background for further research.