Compression and Networking Issues Related to Robust Transmission of Video Over Packet Switched Networks

Abstract

With ever growing network resources, video communication is an important part of today's internet applications. In this research, we developed a spectrum of techniques for unicast and multicast video communication over packet switched networks. These included best effort networks, as well as Quality of Service (QoS) enabled ones, such as those with Diffserv. In doing so, we pay particular attention to video compression techniques, as well as networking issues. Specifically, in the area of video compression, we continued our efforts on application of overcomplete signal expansion schemes to video coding, and explored a number of issues related to matching pursuits based video coding. These include, dictionary approximation, dictionary design, modulus quantization, rate control, multiple description coding and its application to wireless video communication. In the area of video multicast, we proposed the use of hierarchical FEC-as an-error control mechanism that allows receivers to individually trade off latency for received video quality. This scheme is efficient since FEC packets are used to protect only the more important days layers and are multicast only to receivers that need them, thereby improving network utilization. We - perform actual MBONE experiments to evaluate the performance of our scheme.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Nov 01, 2001
Accession Number
ADA425162

Entities

People

  • Avideh Zakhor

Organizations

  • University of California, Berkeley

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Classification
  • Coders
  • Coding
  • Communication Systems
  • Compression
  • Data Compression
  • Dictionaries
  • Electrical Engineering
  • Heterogeneous Networks
  • Internet
  • Networks
  • Packet Loss
  • Sequences
  • Two Dimensional
  • Video Clips

Fields of Study

  • Computer science

Readers

  • Computer Networking
  • Neural Network Machine Learning.