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.