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Fast block matching algorithm based on the winner-update strategy.

Y S Chen1, Y P Hung, C S Fuh

  • 1Inst. of Inf. Sci., Acad. Sinica, Taipei.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 8, 2008
PubMed
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This study introduces a fast block matching algorithm using a winner-update strategy. It significantly speeds up computation while guaranteeing globally optimal matches for applications like motion vector estimation.

Area of Science:

  • Computer Vision
  • Image Processing
  • Algorithm Design

Background:

  • Block matching is crucial for stereo vision, visual tracking, and video compression.
  • Existing fast block matching algorithms often sacrifice guaranteed global optimality for speed.

Purpose of the Study:

  • To present a novel fast block matching algorithm.
  • To ensure global optimality in block matching computations.
  • To improve efficiency in applications like motion vector estimation.

Main Methods:

  • Introduced a winner-update strategy utilizing an ascending lower bound list of matching errors.
  • Employed partial distance and Minkowski's inequality to derive lower bounds.
  • Avoided costly matching error computations when a lower bound exceeds the current global minimum.

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Main Results:

  • Achieved significant speed-up in block matching computations.
  • Guaranteed global optimality for the found matches.
  • Saved 92% to 98% of operations in motion vector estimation experiments on test videos.

Conclusions:

  • The proposed winner-update strategy offers a computationally efficient and globally optimal solution for block matching.
  • The algorithm is adaptable for time-constrained scenarios or for generating ranked candidate matches.
  • Source code is publicly available for further research and application.