Weighted ICP Algorithm for Alignment of Stars from Scanned Astronomical Photographic Plates

Marinov, Alexander; Zlateva, Nadezhda; Dimov, Dimo; Marinov, Delian

Serdica Journal of Computing (2012)

  • Volume: 6, Issue: 1, page 101-110
  • ISSN: 1312-6555

Abstract

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ACM Computing Classification System (1998): I.2.8, I.2.10, I.5.1, J.2.Given the coarse celestial coordinates of the centre of a plate scan and the field of view, we are looking for a mapping between the stars extracted from the image and the stars from a catalogue, where the stars from both sources are represented by their stellar magnitudes and coordinates, relatively to the image centre. In a previous work we demonstrated the application of Iterative Closest Point (ICP) algorithm for the alignment problem where stars were represented only by their geometrical coordinates. ICP leads to translation and rotation of the initial points - a correction required for one set of stars to fit over the other. This paper extends the previous work by demonstrating significant improvement of ICP by using the stellar magnitudes as point weights. The improvement consists of great decrease of the iteration count until convergence, which helps in the case of highly “misaligned” initial states. The essential aspects of the ICP method like noise tolerance of false or missing stars are still in charge.This work is partially supported by the following projects: (1) Creative Development Support of Doctoral Students, Post-Doctoral and Young Researches in the Field of Computer Science, BG 051-PO-001-3.3.04/13, European Social Fund 2007–2013, Operational programme “Human resources development”, and (2) Astroinformatics, grant DO-02-275/2008 of the National Science Fund of the Bulgarian Ministry of Education, Youth and Science.

How to cite

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Marinov, Alexander, et al. "Weighted ICP Algorithm for Alignment of Stars from Scanned Astronomical Photographic Plates." Serdica Journal of Computing 6.1 (2012): 101-110. <http://eudml.org/doc/219659>.

@article{Marinov2012,
abstract = {ACM Computing Classification System (1998): I.2.8, I.2.10, I.5.1, J.2.Given the coarse celestial coordinates of the centre of a plate scan and the field of view, we are looking for a mapping between the stars extracted from the image and the stars from a catalogue, where the stars from both sources are represented by their stellar magnitudes and coordinates, relatively to the image centre. In a previous work we demonstrated the application of Iterative Closest Point (ICP) algorithm for the alignment problem where stars were represented only by their geometrical coordinates. ICP leads to translation and rotation of the initial points - a correction required for one set of stars to fit over the other. This paper extends the previous work by demonstrating significant improvement of ICP by using the stellar magnitudes as point weights. The improvement consists of great decrease of the iteration count until convergence, which helps in the case of highly “misaligned” initial states. The essential aspects of the ICP method like noise tolerance of false or missing stars are still in charge.This work is partially supported by the following projects: (1) Creative Development Support of Doctoral Students, Post-Doctoral and Young Researches in the Field of Computer Science, BG 051-PO-001-3.3.04/13, European Social Fund 2007–2013, Operational programme “Human resources development”, and (2) Astroinformatics, grant DO-02-275/2008 of the National Science Fund of the Bulgarian Ministry of Education, Youth and Science.},
author = {Marinov, Alexander, Zlateva, Nadezhda, Dimov, Dimo, Marinov, Delian},
journal = {Serdica Journal of Computing},
keywords = {Iterative Closest Point (ICP) Algorithm; Stellar Alignment; Weighted Stellar Alignment Astronomical Wide Plate Registration},
language = {eng},
number = {1},
pages = {101-110},
publisher = {Institute of Mathematics and Informatics Bulgarian Academy of Sciences},
title = {Weighted ICP Algorithm for Alignment of Stars from Scanned Astronomical Photographic Plates},
url = {http://eudml.org/doc/219659},
volume = {6},
year = {2012},
}

TY - JOUR
AU - Marinov, Alexander
AU - Zlateva, Nadezhda
AU - Dimov, Dimo
AU - Marinov, Delian
TI - Weighted ICP Algorithm for Alignment of Stars from Scanned Astronomical Photographic Plates
JO - Serdica Journal of Computing
PY - 2012
PB - Institute of Mathematics and Informatics Bulgarian Academy of Sciences
VL - 6
IS - 1
SP - 101
EP - 110
AB - ACM Computing Classification System (1998): I.2.8, I.2.10, I.5.1, J.2.Given the coarse celestial coordinates of the centre of a plate scan and the field of view, we are looking for a mapping between the stars extracted from the image and the stars from a catalogue, where the stars from both sources are represented by their stellar magnitudes and coordinates, relatively to the image centre. In a previous work we demonstrated the application of Iterative Closest Point (ICP) algorithm for the alignment problem where stars were represented only by their geometrical coordinates. ICP leads to translation and rotation of the initial points - a correction required for one set of stars to fit over the other. This paper extends the previous work by demonstrating significant improvement of ICP by using the stellar magnitudes as point weights. The improvement consists of great decrease of the iteration count until convergence, which helps in the case of highly “misaligned” initial states. The essential aspects of the ICP method like noise tolerance of false or missing stars are still in charge.This work is partially supported by the following projects: (1) Creative Development Support of Doctoral Students, Post-Doctoral and Young Researches in the Field of Computer Science, BG 051-PO-001-3.3.04/13, European Social Fund 2007–2013, Operational programme “Human resources development”, and (2) Astroinformatics, grant DO-02-275/2008 of the National Science Fund of the Bulgarian Ministry of Education, Youth and Science.
LA - eng
KW - Iterative Closest Point (ICP) Algorithm; Stellar Alignment; Weighted Stellar Alignment Astronomical Wide Plate Registration
UR - http://eudml.org/doc/219659
ER -

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