Adaptive Quantization Ordering in Feedback Quantization for Interpolative Prediction Coding

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  • Fujita Takahiro
    NIPPON TELEGRAPH AND TELEPHONE WEST CORPORATION Research and Development Center
  • Kubota Akira
    Chuo University, Faculty of Science and Engineering
  • Hatori Yoshinori
    Tokyo Institute of Technology, Interdisciplinary Graduate School of Science and Engineering

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  • 帰還差分量子化を用いた内挿予測符号化における量子化順序の適応制御方式
  • キカン サブン リョウシカ オ モチイタ ナイソウ ヨソク フゴウカ ニ オケル リョウシカ ジュンジョ ノ テキオウ セイギョ ホウシキ

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Abstract

An optimal quantization ordering in the feedback quantization scheme for interpolative prediction coding designed to reduce the coding error power is proposed. This method adaptively selects the optimal quantization order to minimize the coding error power from candidate orders for each one dimensional block of 9x1 pixels. These candidate orders can be determined through a numerical analysis of the coding error with respect to all the quantization orders. Simulation results show that the proposed method can effectively reduce the error power and that selecting the optimal order from only four candidate orders can improve the PSNR by about 2 dB, which is just 0.36 dB below the heighest quality image decoded using all 5040 candidate orders. In the case of two-dimensional blocks, although the numerical analysis shows that the coding error power is almost identical among all the possible orders, simulation results demonstrate that selecting the optimal order from four orders in horizontal and vertical directions improves the PSNR by 2.6dB in the case of an 8×8 block.

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