Neural nets and star/galaxy separation in wide field astronomical images

Author

Andreon, Stefan ; Gargiulo, Giorgio ; Longo, Giuseppe ; Tagliaferri, Roberto ; Capuano, Nicola

Author_Institution

Osservatorio Astron. di Capodimonte, Napoli, Italy

Volume

6

fYear

1999

fDate

36342

Firstpage

3810

Abstract

One of the most relevant problems in the extraction of scientifically useful information from wide field astronomical images (both photographic plates and CCD frames) is the recognition of the objects against a noisy background and their classification in unresolved (starlike) and resolved (galaxies) sources. In this paper we present a neural network based method capable to perform both tasks and discuss in detail the performance of object detection in a representative celestial field. The performance of our method is compared to that of other methodologies often used within the astronomical community

Keywords

astronomy computing; galaxies; neural nets; object recognition; pattern classification; principal component analysis; stars; astronomical images; celestial field; neural network; noisy background; object recognition; pattern classification; principal component analysis; star/galaxy separation; Background noise; Charge coupled devices; Data preprocessing; Neural networks; Neurons; Object detection; Output feedback; Pixel; Principal component analysis; Telescopes;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1999. IJCNN '99. International Joint Conference on

Conference_Location

Washington, DC

ISSN

1098-7576

Print_ISBN

0-7803-5529-6

Type

conf

DOI

10.1109/IJCNN.1999.830761

Filename

830761