Abstract
Efficient streaming of video over wireless networks requires real-time assessment of distortion due to packet loss, especially because predictive coding at the encoder can cause inter-frame propagation of errors and impact the overall quality of the transmitted video. This paper presents an algorithm to evaluate the expected receiver distortion on the source side by utilizing encoder information, transmission channel characteristics and error concealment. Specifically, distinct video transmission units, Group of Blocks (GOBs), are iteratively built at the source by taking into account macroblock coding modes and motion-compensated error concealment for three different combinations of packet loss. Distortion of these units is then calculated using the structural similarity (SSIM) metric and they are stochastically combined to derive the overall expected distortion. The proposed model provides a more accurate estimate of the distortion that closely models quality as perceived through the human visual system. When incorporated into a content-aware utility function, preliminary experimental results show improved packet ordering & scheduling efficiency and overall video signal at the receiver.
Original language | English (US) |
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Title of host publication | Proceedings - 2015 IEEE International Symposium on Multimedia, ISM 2015 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 513-518 |
Number of pages | 6 |
ISBN (Electronic) | 9781509003792 |
DOIs | |
State | Published - Mar 25 2016 |
Event | 17th IEEE International Symposium on Multimedia, ISM 2015 - Miami, United States Duration: Dec 14 2015 → Dec 16 2015 |
Other
Other | 17th IEEE International Symposium on Multimedia, ISM 2015 |
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Country/Territory | United States |
City | Miami |
Period | 12/14/15 → 12/16/15 |
Keywords
- cross-layer optimization
- motion-compensation
- packet scheduling
- structural similarity
- Video quality assessment
ASJC Scopus subject areas
- Computer Science Applications
- Hardware and Architecture
- Software
- Computer Networks and Communications