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An Adaptive Motion Data Storage Reduction Method for Temporal Predictor

  • Ruobing Zou
  • Oscar C. Au
  • Lin Sun
  • Sijin Li
  • Wei Dai
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7088)

Abstract

In the state-of-art video coding standard HEVC, temporal motion vector (MV) predictor is adopted in order to improve coding efficiency. However, motion vector information in reference frames, which is used by temporal MV predictor, takes significant amount of bits in memory storage. Therefore motion data needs to be compressed before storing into buffer. In this paper we propose an adaptive motion data storage reduction method. First, it divides the current 16x16 block in the reference frame into four partitions. One MV is sampled from each partition and all sampled MVs form a MV candidate set. Then it judges if one or two MVs should be stored into the MV buffer by checking the maximum distance between any two of the MVs in the candidate set. If the maximum distance is greater than a certain threshold, the motion data of the two MVs that have maximum distance are put into memory; otherwise the motion data of the upper left block is stored. The basic goal of the proposed method is to improve the accuracy of temporal MV predictor at the same time reducing motion data memory size. Simulation results show that compared to the original HEVC MV memory compression method in the 4th JCT-VC meeting, the proposed scheme achieves a coding gain of 0.5%~0.6%; and the memory size is reduced by more than 87.5% comparing to without using motion data compression.

Keywords

HEVC MV data storage MV compression temporal predictor 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Ruobing Zou
    • 1
  • Oscar C. Au
    • 1
  • Lin Sun
    • 1
  • Sijin Li
    • 1
  • Wei Dai
    • 1
  1. 1.Department of Electronic and Computer EngineeringHong Kong University of Science and TechnologyKowloonHong Kong

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