Institute of Mathematics and Informatics Bulgarian Academy of Sciences
Serdica Journal of Computing, Vol. 6, No 1, (2012), 101p-110p
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.
ACM Computing Classification System (1998): I.2.8, I.2.10, I.5.1, J.2.