  Astronomical images are of crucial importance for astronomers since they
contain a lot of information about celestial bodies that can not be directly
accessible. Most of the information available for the analysis of these objects
starts with sky explorations via telescopes and satellites. Unfortunately, the
quality of astronomical images is usually very low with respect to other real
images and this is due to technical and physical features related to their
acquisition process. This increases the percentage of noise and makes more
difficult to use directly standard segmentation methods on the original image.
In this work we will describe how to process astronomical images in two steps:
in the first step we improve the image quality by a rescaling of light
intensity whereas in the second step we apply level-set methods to identify the
objects. Several experiments will show the effectiveness of this procedure and
the results obtained via various discretization techniques for level-set
equations.

Numerical Analysis;Numerical Analysis