Publication detail

Iterative Phase Correlation Algorithm for High-precision Subpixel Image Registration

HRAZDÍRA, Z. DRUCKMÜLLER, M. HABBAL, S.

Original Title

Iterative Phase Correlation Algorithm for High-precision Subpixel Image Registration

English Title

Iterative Phase Correlation Algorithm for High-precision Subpixel Image Registration

Type

journal article in Web of Science

Language

en

Original Abstract

Many astrophysical observations and measurement techniques that rely on data from images include an image registration step. The results of such techniques thus heavily rely on the precision of the registration. We present an Iterative Phase Correlation (IPC) algorithm, which is an extension of the well-known phase correlation method of image registration and is ideally suited for problems, where the subpixel registration accuracy plays a crucial role. Furthermore, a sophisticated and reliable method of optimal IPC parameter estimation is described. The paper includes examples of such optimized parameters for Solar Dynamics Observatory (SDO)/Helioseismic and Magnetic Imager, SDO/Atmospheric Imaging Assembly, and Solar Terrestrial Relations Observatory A/B Sun Earth Connection Coronal and Heliospheric Investigation images. The new method (both with or without the parameter optimization step) significantly outperforms standard image registration methods, such as (non-iterative) phase correlation or (normalized) cross correlation in the sense of subpixel accuracy. A step-by-step pseudocode implementation is also included.

English abstract

Many astrophysical observations and measurement techniques that rely on data from images include an image registration step. The results of such techniques thus heavily rely on the precision of the registration. We present an Iterative Phase Correlation (IPC) algorithm, which is an extension of the well-known phase correlation method of image registration and is ideally suited for problems, where the subpixel registration accuracy plays a crucial role. Furthermore, a sophisticated and reliable method of optimal IPC parameter estimation is described. The paper includes examples of such optimized parameters for Solar Dynamics Observatory (SDO)/Helioseismic and Magnetic Imager, SDO/Atmospheric Imaging Assembly, and Solar Terrestrial Relations Observatory A/B Sun Earth Connection Coronal and Heliospheric Investigation images. The new method (both with or without the parameter optimization step) significantly outperforms standard image registration methods, such as (non-iterative) phase correlation or (normalized) cross correlation in the sense of subpixel accuracy. A step-by-step pseudocode implementation is also included.

Keywords

phase correlation, optimization, sub-pixel registration

Released

20.02.2020

Publisher

IOP PUBLISHING LTD

Location

BRISTOL

Pages from

247

Pages to

255

Pages count

8

URL

Documents

BibTex


@article{BUT164310,
  author="Zdeněk {Hrazdíra} and Miloslav {Druckmüller} and Shadia Rifai {Habbal}",
  title="Iterative Phase Correlation Algorithm for High-precision Subpixel Image Registration",
  annote="Many astrophysical observations and measurement techniques that rely on data from images include an image registration step. The results of such techniques thus heavily rely on the precision of the registration. We present an Iterative Phase Correlation (IPC) algorithm, which is an extension of the well-known phase correlation method of image registration and is ideally suited for problems, where the subpixel registration accuracy plays a crucial role. Furthermore, a sophisticated and reliable method of optimal IPC parameter estimation is described. The paper includes examples of such optimized parameters for Solar Dynamics Observatory (SDO)/Helioseismic and Magnetic Imager, SDO/Atmospheric Imaging Assembly, and Solar Terrestrial Relations Observatory A/B Sun Earth Connection Coronal and Heliospheric Investigation images. The new method (both with or without the parameter optimization step) significantly outperforms standard image registration methods, such as (non-iterative) phase correlation or (normalized) cross correlation in the sense of subpixel accuracy. A step-by-step pseudocode implementation is also included.",
  address="IOP PUBLISHING LTD",
  chapter="164310",
  doi="10.3847/1538-4365/ab63d7",
  howpublished="print",
  institution="IOP PUBLISHING LTD",
  number="1",
  volume="247",
  year="2020",
  month="february",
  pages="247--255",
  publisher="IOP PUBLISHING LTD",
  type="journal article in Web of Science"
}