Layered Wyner - Ziv Video Coding for Noisy Channels

نویسندگان

  • QIAN XU
  • Zixiang Xiong
  • Costas N. Georghiades
  • Andrew K. Chan
  • Dmitri Loguinov
  • Chanan Singh
  • Qian Xu
چکیده

Layered Wyner-Ziv Video Coding for Noisy Channels. (August 2004) Qian Xu, B.S., University of Science & Technology of China Chair of Advisory Committee: Dr. Zixiang Xiong The growing popularity of video sensor networks and video celluar phones has generated the need for low-complexity and power-efficient multimedia systems that can handle multiple video input and output streams. While standard video coding techniques fail to satisfy these requirements, distributed source coding is a promising technique for “uplink” applications. Wyner-Ziv coding refers to lossy source coding with side information at the decoder. Based on recent theoretical result on successive Wyner-Ziv coding, we propose in this thesis a practical layered Wyner-Ziv video codec using the DCT, nested scalar quantizer, and irregular LDPC code based Slepian-Wolf coding (or lossless source coding with side information) for noiseless channel. The DCT is applied as an approximation to the conditional KLT, which makes the components of the transformed block conditionally independent given the side information. NSQ is a binning scheme that facilitates layered bit-plane coding of the bin indices while reducing the bit rate. LDPC code based Slepian-Wolf coding exploits the correlation between the quantized version of the source and the side information to achieve further compression. Different from previous works, an attractive feature of our proposed system is that video encoding is done only once but decoding allowed at many lower bit rates without quality loss. For Wyner-Ziv coding over discrete noisy channels, we present a Wyner-Ziv video codec using IRA codes for Slepian-Wolf coding based on the idea of two equivalent channels. For video streaming applications where the channel is packet based, we apply unequal error protection scheme to the embedded Wyner-Ziv coded video stream to find the optimal source-channel coding

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تاریخ انتشار 2004