Hierarchical region-based image registration in scale space

Nan Jiang, Jennie Si, Glen Abousleman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

This paper presents a new method for image registration for real natural scenes. The method is based on the observation that most natural scenes are actually 3-D. If the assumption of weak perspective is violated, the error in image registration induced by parallax is increased, leading artifacts or blurs in image mosaic. Our method first applies the affine-invariant point detector in scale space. After clustering feature point pairs, an initial global transformation is formed based on majority correspondence. The global transformation is evaluated in each region at certain scale determined by inliers. The global model is optimized for local registration by minimizing Least Square Error. This method is more robust than standard image registration algorithms on images subject to uncalibrated camera motion.

Original languageEnglish (US)
Title of host publication2006 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings
PagesII745-II748
StatePublished - Dec 1 2006
Event2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006 - Toulouse, France
Duration: May 14 2006May 19 2006

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2
ISSN (Print)1520-6149

Other

Other2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006
CountryFrance
CityToulouse
Period5/14/065/19/06

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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