Fast image registration by hierarchical soft correspondence detection

Research output: Contribution to journalArticle

20 Citations (Scopus)

Abstract

A new approach, based on the hierarchical soft correspondence detection, has been presented for significantly improving the speed of our previous HAMMER image registration algorithm. Currently, HAMMER takes a relative long time, e.g., up to 80 min, to register two regular sized images using Linux machine (with 2.40 GHz CPU and 2-Gbyte memory). This is because the results of correspondence detection, used to guide the image warping, can be ambiguous in complex structures and thus the image warping has to be conservative and accordingly takes long time to complete. In this paper, a hierarchical soft correspondence detection technique has been employed to detect correspondences more robustly, thereby allowing the image warping to be completed straightforwardly and fast. By incorporating this hierarchical soft correspondence detection technique into the HAMMER registration framework, both the robustness and the accuracy of registration (in terms of low average registration error) can be achieved. Experimental results on real and simulated data show that the new registration algorithm, based on the hierarchical soft correspondence detection, can run nine times faster than HAMMER while keeping the similar registration accuracy.

Original languageEnglish
Pages (from-to)954-961
Number of pages8
JournalPattern Recognition
Volume42
Issue number5
DOIs
Publication statusPublished - 2009 May

Keywords

  • Deformable registration
  • Feature matching
  • Local descriptor
  • Non-rigid registration

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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