Repository logo

Infoscience

  • English
  • French
Log In
Logo EPFL, École polytechnique fédérale de Lausanne

Infoscience

  • English
  • French
Log In
  1. Home
  2. Academic and Research Output
  3. Journal articles
  4. Modeling and Analysis of Distortion Caused by Markov-Model Burst Packet Losses in Video Transmission
 
research article

Modeling and Analysis of Distortion Caused by Markov-Model Burst Packet Losses in Video Transmission

Li, Z.
•
Chakareski, J.
•
Niu, X.
Show more
2009
IEEE Transactions on Circuits and Systems for Video Technology

This paper addresses the problem of distortion modeling for video transmission over burst-loss channels characterized by a finite state Markov chain. Based on a detailed analysis of the error propagation and the bursty losses, a Distortion Trellis model is proposed, enabling us to estimate at both frame level and sequence level the expected mean-square error (MSE) distortion caused by Markov-model bursty packet losses. The model takes into account the temporal dependencies induced by both the motion compensated coding scheme and the Markov-model channel losses. The model is applicable to most block-based motion compensated encoders, and most Markovmodel lossy channels as long as the loss pattern probabilities for that channel is computable. Based on the study of the decaying behavior of the error propagation, 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 factors such as 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 the data produced from realistic networks loss traces. The experiment results demonstrate that the proposed model is also accurate in estimating the expected distortion for video transmission in real networks.

  • Files
  • Details
  • Metrics
Loading...
Thumbnail Image
Name

04914864.pdf

Access type

openaccess

Size

1.21 MB

Format

Adobe PDF

Checksum (MD5)

076cfcc5a14ad7708f8f5eb22fa3ac98

Logo EPFL, École polytechnique fédérale de Lausanne
  • Contact
  • infoscience@epfl.ch

  • Follow us on Facebook
  • Follow us on Instagram
  • Follow us on LinkedIn
  • Follow us on X
  • Follow us on Youtube
AccessibilityLegal noticePrivacy policyCookie settingsEnd User AgreementGet helpFeedback

Infoscience is a service managed and provided by the Library and IT Services of EPFL. © EPFL, tous droits réservés