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Region-adaptive probability model selection for the arithmetic coding of video texture

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Abstract
In video coding systems using adaptive arithmetic coding to compress texture information, the employed symbol probability models need to be retrained every time the coding process moves into an area with different texture. To avoid this inefficiency, we propose to replace the probability models used in the original coder with multiple switchable sets of probability models. We determine the model set to use in each spatial region in an optimal manner, taking into account the additional signaling overhead. Experimental results show that this approach, when applied to H. 264/AVC's context-based adaptive binary arithmetic coder (CABAC), yields significant bit-rate savings, which are comparable to or higher than those obtained using alternative improvements to CABAC previously proposed in the literature.
Keywords
CABAC, arithmetic coding, Video coding, STANDARD, context modeling, adaptivity

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Chicago
Vermeirsch, Kenneth, Joeri Barbarien, Peter Lambert, and Rik Van de Walle. 2011. “Region-adaptive Probability Model Selection for the Arithmetic Coding of Video Texture.” In International Conference on Acoustics Speech and Signal Processing ICASSP, 1537–1540. New York, NY, USA: IEEE.
APA
Vermeirsch, Kenneth, Barbarien, J., Lambert, P., & Van de Walle, R. (2011). Region-adaptive probability model selection for the arithmetic coding of video texture. International Conference on Acoustics Speech and Signal Processing ICASSP (pp. 1537–1540). Presented at the 36th International conference on Acoustics, Speech and Signal Processing (ICASSP 2011), New York, NY, USA: IEEE.
Vancouver
1.
Vermeirsch K, Barbarien J, Lambert P, Van de Walle R. Region-adaptive probability model selection for the arithmetic coding of video texture. International Conference on Acoustics Speech and Signal Processing ICASSP. New York, NY, USA: IEEE; 2011. p. 1537–40.
MLA
Vermeirsch, Kenneth, Joeri Barbarien, Peter Lambert, et al. “Region-adaptive Probability Model Selection for the Arithmetic Coding of Video Texture.” International Conference on Acoustics Speech and Signal Processing ICASSP. New York, NY, USA: IEEE, 2011. 1537–1540. Print.
@inproceedings{1250721,
  abstract     = {In video coding systems using adaptive arithmetic coding to compress texture information, the employed symbol probability models need to be retrained every time the coding process moves into an area with different texture. To avoid this inefficiency, we propose to replace the probability models used in the original coder with multiple switchable sets of probability models. We determine the model set to use in each spatial region in an optimal manner, taking into account the additional signaling overhead. Experimental results show that this approach, when applied to H. 264/AVC's context-based adaptive binary arithmetic coder (CABAC), yields significant bit-rate savings, which are comparable to or higher than those obtained using alternative improvements to CABAC previously proposed in the literature.},
  author       = {Vermeirsch, Kenneth and Barbarien, Joeri and Lambert, Peter and Van de Walle, Rik},
  booktitle    = {International Conference on Acoustics Speech and Signal Processing ICASSP},
  isbn         = {9781457705373},
  issn         = {1520-6149},
  keyword      = {CABAC,arithmetic coding,Video coding,STANDARD,context modeling,adaptivity},
  language     = {eng},
  location     = {Prague, Czech Republic},
  pages        = {1537--1540},
  publisher    = {IEEE},
  title        = {Region-adaptive probability model selection for the arithmetic coding of video texture},
  year         = {2011},
}

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