Scalable predictive coding by nested quantization with layered side information (TP-S1)

Author(s) : Huisheng Wang (Signal and Image Processing Institute, Department of Electrical Engineering, University of Southern California, USA) Antonio Ortega (Signal and Image Processing Institute, Department of Electrical Engineering, University of Southern California, USA)

Abstract : An efficient scalable predictive coding method is proposed for the Wyner-Ziv problem, using nested lattice quantization followed by multi-layer Slepian-Wolf coders (SWC) with layered side information. The proposed coder can support embedded representation and high coding efficiency by using the high quality version of the previous frame as side information in the enhancement-layer coding of the current frame. Experiments based on a DPCM model show substantial improvement on the PSNR of the enhancement layer reconstruction. The paper also discusses the possible adaptation of this approach to the practical video compression.

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