Image registration method based on local high order approach

Yannan WU, Oscar C. AU, Enming LUO, Chi Ho YEUNG, Shing Fat TU

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Image registration based on gradient and least square optimization technique is one of the most edge-cutting registration algorithms. Such method, especially useful for subpixel motion, searches for the best motion in an iterative way. This paper solves the same motion registration problem following this direction. And the well-known Gauss-Newton method (GNM) is employed here as the optimization tool. To achieve a speed-up and reduction of the arithmetic calculation, a simplified high order approach(SHoA) used to calculate several parameters for GNM is introduced. Detailed complexity analysis and performance comparison are presented showing that such an approach is a better trade-off between registration error and the number of math operations. Copyright © 2009 IEEE.

Original languageEnglish
Title of host publication2009 IEEE International Symposium on Circuits and Systems, ISCAS 2009
Place of PublicationPiscataway
PublisherIEEE
Pages746-749
ISBN (Electronic)9781424438280
ISBN (Print)9781424438273
DOIs
Publication statusPublished - 2009

Fingerprint

Image registration
Newton-Raphson method

Citation

Wu, Y., Au, O. C., Luo, E., Yeung, C.-H., & Tu, S.-F. (2009). Image registration method based on local high order approach. In 2009 IEEE International Symposium on Circuits and Systems, ISCAS 2009 (pp. 746-749). Piscataway: IEEE.

Keywords

  • Image registration
  • Optimization methods
  • Least squares methods
  • Iterative methods
  • Newton method
  • Recursive estimation
  • Video compression
  • Motion estimation
  • Interpolation
  • Gradient methods