An approach of point sources detection in X-ray astronomical image using support vector machine

• Main Authors: MA Zhixian, WU Zhongyao, YOU hanxu, ZHU Jie
• Format: Article
• Language: English
• Published: Academic Journals Center of Shanghai Normal University 2016-04-01
• Series: Journal of Shanghai Normal University (Natural Sciences)
• Subjects: X-ray point sources; thresholding; peak detection; support vector machine; spectrum
• Online Access: http://qktg.shnu.edu.cn/zrb/shsfqkszrb/ch/reader/create_pdf.aspx?file_no=201602017&flag=1&year_id=2016&quarter_id=2
• ISSN: 1000-5137; 1000-5137

Since most of energy sources in our Universe appear point-like structures,the study of point sources detection method on astronomical images has become significant.In this paper,a point sources detection approach on X-ray astronomical image was proposed.Firstly,a thresholding method was used to separate the background noises.Then,the peak detection method was taken to detect the positions of potential point sources.After that,we extracted spectrum features of point sources and backgrounds,and generated the classification model using the Support Vector Machine.Finally,the correct point sources were got after discarding of spurious detections with the classification model.Our approach was applied to the X-ray image of Galaxy NGC 4552.Compared with “wavdetect”,our approach has the same performance of accuracy with a detection error rate of 5%,but a higher efficiency.