A Fast Motion Estimation Algorithm Based on Diamond and Simplified Square Search Patterns

  • Yun Cheng
  • Kui Dai
  • Zhiying Wang
  • Jianjun Guo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3773)

Abstract

Based on the directional characteristic of SAD(Sum of Absolute Difference) distribution and the center-biased characteristic of motion vectors, a fast BMA(block-matching motion estimation algorithm), DSSS(Diamond and Simplified Square Search), is proposed in this paper. DSSS employs line search pattern(LP), triangle search pattern(TP), or square pattern(SP) adaptively according to the distance between the MBD(Minimum Block Distortion) and SMBD(Second MBD) points to locate the best matching block with large motion vector, and diamond search pattern(DP) to refine the motion vector. Although the proposed DSSS may also be trapped in local minima, the experimental results show that it is faster than DS(Diamond Search) and DTS(Diamond and Triangle Search), while its encoding efficiency is better than DS and it is almost the same as that of DTS.

Keywords

Motion Vector Motion Estimation Search Pattern Quantization Parameter Check Point 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Yun Cheng
    • 1
    • 2
  • Kui Dai
    • 2
  • Zhiying Wang
    • 2
  • Jianjun Guo
    • 2
  1. 1.Department of Information EngineeringHunan Institute of Humanities, Science and TechnologyLoudiChina
  2. 2.College of ComputerNational University of Defense TechnologyChangshaChina

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