DocumentCode :
1807659
Title :
GOP-Level Transmission Distortion Modeling for Video Streaming over Mobile Networks
Author :
Han, Yu ; Men, Aidong ; Chang, Kan ; Quan, Ziyi
Author_Institution :
Sch. of Inf. & Telecommun. Eng., Beijing Univ. of Posts & Telecommun., Beijing, China
Volume :
1
fYear :
2009
fDate :
18-20 Aug. 2009
Firstpage :
91
Lastpage :
95
Abstract :
A major challenge in video coding and transmission over mobile networks is that the wireless channel is error-prone and the channel resources are limited. In this work, we analyze the picture distortion caused by channel errors and the distortion propagation behavior in its subsequent frames along the motion prediction path. We propose a linear fitting approach algorithm to achieve a low complexity GOP-level transmission distortion modeling. It is a predictive modeling which allows the encoder to predict the transmission distortion before the whole GOP is compressed and transmitted. The simulation results demonstrate that the proposed modeling has low computational complexity and high accuracy. It can be used in allocating the limited channel resources optimally for mobile video applications.
Keywords :
channel coding; data compression; image motion analysis; mobile radio; video coding; video communication; video streaming; wireless channels; GOP-level transmission distortion modeling; channel errors; channel resources; computational complexity; distortion propagation behavior; linear fitting algorithm; mobile networks; motion prediction path; picture distortion; predictive modeling; video coding; video compression; video streaming; video transmission; wireless channel; Bandwidth; Computational modeling; Decoding; Predictive models; Propagation losses; Resource management; Streaming media; Video coding; Video compression; Video sequences; mobile network; predictive modeling; transmission distortion; video coding;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Assurance and Security, 2009. IAS '09. Fifth International Conference on
Conference_Location :
Xian
Print_ISBN :
978-0-7695-3744-3
Type :
conf
DOI :
10.1109/IAS.2009.107
Filename :
5283423
Link To Document :
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