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dc.contributor.advisorJiang, Jianmin
dc.contributor.advisorMin, Geyong
dc.contributor.authorJayaseelan, John*
dc.date.accessioned2013-11-28T18:02:12Z
dc.date.available2013-11-28T18:02:12Z
dc.date.issued2013-11-28
dc.identifier.urihttp://hdl.handle.net/10454/5729
dc.description.abstractWhile there has always been a tremendous demand for streaming video over Wireless networks, the nature of the application still presents some challenging issues. These applications that transmit coded video sequence data over best-effort networks like the Internet, the application must cope with the changing network behaviour; especially, the source encoder rate should be controlled based on feedback from a channel estimator that explores the network intermittently. The arrival of powerful video compression techniques such as H.264, which advance in networking and telecommunications, opened up a whole new frontier for multimedia communications. The aim of this research is to transmit the H.264 coded video frames in the wireless network with maximum reliability and in a very efficient manner. When the H.264 encoded video sequences are to be transmitted through wireless network, it faces major difficulties in reaching the destination. The characteristics of H.264 video coded sequences are studied fully and their capability of transmitting in wireless networks are examined and a new approach called Optimal Packet Fragmentation (OPF) is framed and the H.264 coded sequences are tested in the wireless simulated environment. This research has three major studies involved in it. First part of the research has the study about Long Range Dependence (LRD) and the ways by which the self-similarity can be estimated. For estimating the LRD a few studies are carried out and Wavelet-based estimator is selected for the research because Wavelets incarcerate both time and frequency features in the data and regularly provides a more affluent picture than the classical Fourier analysis. The Wavelet used to estimate the self-similarity by using the variable called Hurst Parameter. Hurst Parameter tells the researcher about how a data can behave inside the transmitted network. This Hurst Parameter should be calculated for a more reliable transmission in the wireless network. The second part of the research deals with MPEG-4 and H.264 encoder. The study is carried out to prove which encoder is superior to the other. We need to know which encoder can provide excellent Quality of Service (QoS) and reliability. This study proves with the help of Hurst parameter that H.264 is superior to MPEG-4. The third part of the study is the vital part in this research; it deals with the H.264 video coded frames that are segmented into optimal packet size in the MAC Layer for an efficient and more reliable transfer in the wireless network. Finally the H.264 encoded video frames incorporated with the Optimal Packet Fragmentation are tested in the NS-2 wireless simulated network. The research proves the superiority of H.264 video encoder and OPF¿s master class.en_US
dc.language.isoenen_US
dc.rights<a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/"><img alt="Creative Commons License" style="border-width:0" src="http://i.creativecommons.org/l/by-nc-nd/3.0/88x31.png" /></a><br />The University of Bradford theses are licenced under a <a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/">Creative Commons Licence</a>.eng
dc.subjectVideo compression techniquesen_US
dc.subjectTelecommunicationsen_US
dc.subjectNetworksen_US
dc.subjectH.264 video coded sequencesen_US
dc.subjectWireless networksen_US
dc.subjectOptimal Packet Fragmentation (OPF)en_US
dc.subjectQuality of Service (QoS)en_US
dc.subjectVideo encoderen_US
dc.titleEstimation of LRD present in H.264 video traces using wavelet analysis and proving the paramount of H.264 using OPF technique in wi-fi environment.en_US
dc.type.qualificationleveldoctoralen_US
dc.publisher.institutionUniversity of Bradfordeng
dc.publisher.departmentDepartment of Electronic Imaging and Media Communicationsen_US
dc.typeThesiseng
dc.type.qualificationnamePhDen_US
dc.date.awarded2012
refterms.dateFOA2018-07-19T12:58:15Z


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