Optimizing image registration by mutually exclusive scale components

Terrence Chen, Thomas S. Huang

Research output: Contribution to conferencePaperpeer-review

Abstract

Local optimum has been one of the most difficult problems in image registration notwithstanding the extensive research effort that has been put into solving it. Local optimums occur when a portion of patterns in the floating image coincide with a portion of patterns in the reference image even though the two images are not entirely marched. Existing hierarchical or multi-scale methods suffer from this problem mainly because some redundant information that causes local optimums appears in multiple scales. We propose to avoid it by decomposing an image into several mutually exclusive scale components so that minimal redundant information is present. Our method is evaluated and compared with existing methods using high resolution satellite imagery where thousands of local optimum traps are hidden. We show that our method has significant improvement over existing solutions in both robustness and efficiency.

Original languageEnglish (US)
DOIs
StatePublished - 2007
Event2007 IEEE 11th International Conference on Computer Vision, ICCV - Rio de Janeiro, Brazil
Duration: Oct 14 2007Oct 21 2007

Other

Other2007 IEEE 11th International Conference on Computer Vision, ICCV
Country/TerritoryBrazil
CityRio de Janeiro
Period10/14/0710/21/07

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

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