Video compression is necessary for effective coding of video data so that the data can be stored or transmitted more efficiently. In video compression, the more redundant data are discarded, the higher compression ratios will be achievable. This causes the contents of a compressed bitstream to be highly dependent on each other. In video communications, the compressed bitstream is ,subject to losses and errors due to the nature of the transmission medium. Since the contents of the compressed bitstream are highly dependent on each other, when a loss or an error occurs this leads to propagation of the error, which causes deterioration of the decoded video quality. Error resilience plays an important role / in decreasing the quality degradation caused by losses arid errors. Error resilience methods can either take place in the encoder side as a coding technique which decreases the effects of errors on the coded bitstream or in the decoder side as a technique which conceals the detected errors or losses. Error concealment which takes place in decoder side and redundant slice coding which takes place in encoder side are investigated throughout the thesis. The first part of the thesis investigates efficient error concealment techniques for Scalable Video Coding (SVC). These include the utilisation of higher Temporal Level picture motion information and the utilisation of "Bridge Pictures" which will be described in later chapters, for error concealment. The second part of the thesis investigates redundant slice coding for SVc. Single Block per Macroblock and Zero Residual redundant slice coding schemes are proposed and tested in this part of the thesis. In addition to these, an adaptive redundant slice allocation scheme is also proposed and tested. The last part of the thesis investigates error resilient coding techniques for multi-view 3D video. Multi-view 3D video compression is achieved using the SVC CoDec by coding one of the views as the Base Layer and the other views as the Enhancement Layers utilising the adaptive inter-layer prediction mechanism of the SVc.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:582748 |
Date | January 2014 |
Creators | Dereboylu, Ziya |
Publisher | University of Surrey |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
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