Data modeling of deep sky images

James Handley; Holger M. Jaenisch; Albert C. Lim; Graeme L. White; Alex Hons; Miroslav Filipovic; Matthew Edwards; Simon C. Craig; Martin J. Cullum

Data modeling of deep sky images

James Handley, Holger M. Jaenisch, Albert C. Lim, Graeme L. White, Alex Hons, Miroslav Filipovic, Matthew Edwards, Simon C. Craig, Martin J. Cullum

Research output: Chapter in Book / Conference Paper › Conference Paper

Abstract

We present a method for simulating CCD focal plane array (FPA) images of extended deep sky objects using Data Modeling. Data Modeling is a process of deriving functional equations from measured data. These tools are used to model FPA fixed pattern noise, shot noise, non-uniformity, and the extended objects themselves. The mathematical model of the extended object is useful for correlation analysis and other image understanding algorithms used in Virtual Observatory Data Mining. We apply these tools to the objects in the Messier list and build a classifier that achieves 100% correct classification.

Original language	English
Title of host publication	Modeling and Systems Engineering for Astronomy: Proceedings of the SPIE -The International Society for Optical Engineering. Vol. 5497
Publisher	SPIE--The International Society for Optical Engineering
Number of pages	12
Publication status	Published - 2004
Event	Modeling and Systems Engineering for Astronomy - Duration: 1 Jan 2004 → …

Conference

Conference	Modeling and Systems Engineering for Astronomy
Period	1/01/04 → …

Keywords

deep sky
data modeling
astronomy
image modeling
National Virtual Observatory (U.S.)
Messier classification

Cite this

@inproceedings{38fb0cdef4da4ec29b31a164ada25af0,

title = "Data modeling of deep sky images",

abstract = "We present a method for simulating CCD focal plane array (FPA) images of extended deep sky objects using Data Modeling. Data Modeling is a process of deriving functional equations from measured data. These tools are used to model FPA fixed pattern noise, shot noise, non-uniformity, and the extended objects themselves. The mathematical model of the extended object is useful for correlation analysis and other image understanding algorithms used in Virtual Observatory Data Mining. We apply these tools to the objects in the Messier list and build a classifier that achieves 100% correct classification.",

keywords = "deep sky, data modeling, astronomy, image modeling, National Virtual Observatory (U.S.), Messier classification",

author = "James Handley and Jaenisch, {Holger M.} and Lim, {Albert C.} and White, {Graeme L.} and Alex Hons and Miroslav Filipovic and Matthew Edwards and Craig, {Simon C.} and Cullum, {Martin J.}",

year = "2004",

language = "English",

booktitle = "Modeling and Systems Engineering for Astronomy: Proceedings of the SPIE -The International Society for Optical Engineering. Vol. 5497",

publisher = "SPIE--The International Society for Optical Engineering",

note = "Modeling and Systems Engineering for Astronomy ; Conference date: 01-01-2004",

}

Handley, J, Jaenisch, HM, Lim, AC, White, GL, Hons, A, Filipovic, M, Edwards, M, Craig, SC & Cullum, MJ 2004, Data modeling of deep sky images. in Modeling and Systems Engineering for Astronomy: Proceedings of the SPIE -The International Society for Optical Engineering. Vol. 5497. SPIE--The International Society for Optical Engineering, Modeling and Systems Engineering for Astronomy, 1/01/04.

TY - GEN

T1 - Data modeling of deep sky images

AU - Handley, James

AU - Jaenisch, Holger M.

AU - Lim, Albert C.

AU - White, Graeme L.

AU - Hons, Alex

AU - Filipovic, Miroslav

AU - Edwards, Matthew

AU - Craig, Simon C.

AU - Cullum, Martin J.

PY - 2004

Y1 - 2004

N2 - We present a method for simulating CCD focal plane array (FPA) images of extended deep sky objects using Data Modeling. Data Modeling is a process of deriving functional equations from measured data. These tools are used to model FPA fixed pattern noise, shot noise, non-uniformity, and the extended objects themselves. The mathematical model of the extended object is useful for correlation analysis and other image understanding algorithms used in Virtual Observatory Data Mining. We apply these tools to the objects in the Messier list and build a classifier that achieves 100% correct classification.

AB - We present a method for simulating CCD focal plane array (FPA) images of extended deep sky objects using Data Modeling. Data Modeling is a process of deriving functional equations from measured data. These tools are used to model FPA fixed pattern noise, shot noise, non-uniformity, and the extended objects themselves. The mathematical model of the extended object is useful for correlation analysis and other image understanding algorithms used in Virtual Observatory Data Mining. We apply these tools to the objects in the Messier list and build a classifier that achieves 100% correct classification.

KW - deep sky

KW - data modeling

KW - astronomy

KW - image modeling

KW - National Virtual Observatory (U.S.)

KW - Messier classification

UR - http://handle.uws.edu.au:8081/1959.7/45073

M3 - Conference Paper

BT - Modeling and Systems Engineering for Astronomy: Proceedings of the SPIE -The International Society for Optical Engineering. Vol. 5497

PB - SPIE--The International Society for Optical Engineering

T2 - Modeling and Systems Engineering for Astronomy

Y2 - 1 January 2004

ER -

Data modeling of deep sky images

Abstract

Conference

Keywords

Other files and links

Fingerprint

Cite this