Cosmic Ray Background Detection and Removal from CCD Images using Neural Networks

Document Type : Original Article

Authors

1 Dept. of CS Faculty of Computer and Information, Zagazig University

2 Dept. of CS Faculty of Computer and Artificial Intelligence, University of Sadat City

Abstract

Over the last few years, Artificial Neural Networks (ANN) indicate favorable characterizations in accuracy and performance in different scientific fields, especially space since, Astrophysics- and physics. To obtain better quality of astronomical images the signatures of transient artifacts such as noise, cosmic rays, satellite trails and scattered cosmic light must be removed in the preprocessing operation. In this study we have developed an Artificial Neural Network (ANN) model for detection and removing the cosmic ray from the astronomical and space CCD images. The ANN proposed algorithm has been trained and tested using observational CCD image of data came from actual astronomical observations with the CCD camera system at kottamia 74 inch astronomical telescope in Egypt. We have been use this technique to identify, on a pixel-by-pixel level. The algorithm can be applied to any survey images. Also our result showing that the large amount of data give the more accuracy of results, it is also very fast in comparison with other algorithms found in astronomical data-processing.

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