Modeling of distortion caused by Markov-model burst packet losses in video transmission

Zhicheng Li, Jacob Chakareski, Xiaodun Niu, Yongjun Zhang, Wanyi Gu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

Abstract

This paper addresses the problem of distortion modeling for video transmission over burst-loss channels characterized by a finite state Markov chain. A Distortion Trellis model is proposed, enabling us to estimate at the frame level the expected mean-square error (MSE) distortion caused by Markov-model bursty packet losses. A sliding window algorithm is developed to perform the MSE estimation with low complexity. Simulation results show that the proposed models are accurate for all tested average loss rates and average burst lengths. Based on the experimental results, the proposed techniques are used to analyze the impact of average burst length on the average decoded video quality. The proposed model is further extended to a more general form, and the modeled distortion is compared with simulation data. These experiments demonstrate that the extended model is also accurate for all tested loss rates.

Original languageEnglish (US)
Title of host publication2009 IEEE International Workshop on Multimedia Signal Processing, MMSP '09
DOIs
StatePublished - 2009
Externally publishedYes
Event2009 IEEE International Workshop on Multimedia Signal Processing, MMSP '09 - Rio De Janeiro, Brazil
Duration: Oct 5 2009Oct 7 2009

Publication series

Name2009 IEEE International Workshop on Multimedia Signal Processing, MMSP '09

Conference

Conference2009 IEEE International Workshop on Multimedia Signal Processing, MMSP '09
Country/TerritoryBrazil
CityRio De Janeiro
Period10/5/0910/7/09

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Signal Processing

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