Automated object detection for astronomical images

Details Automated object detection for astronomical images Automated object detection for astronomical images

Oct 2005

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2005spie.6015..314o&link_type=abstract

Multimedia Systems and Applications VIII. Edited by Vetro, Anthony; Chen, Chang Wen; Kuo, C.-C. J.; Zhang, Tong; Tian, Qi; Smit

Computer Science

Multimedia

Scientific paper

Sponsored by the National Aeronautical Space Association (NASA), the Synergetic Education and Research in Enabling NASA-centered Academic Development of Engineers and Space Scientists (SERENADES) Laboratory was established at California State University, Los Angeles (CSULA). An important on-going research activity in this lab is to develop an easy-to-use image analysis software with the capability of automated object detection to facilitate astronomical research. This paper presented a fast object detection algorithm based on the characteristics of astronomical images. This algorithm consists of three steps. First, the foreground and background are separated using histogram-based approach. Second, connectivity analysis is conducted to extract individual object. The final step is post processing which refines the detection results. To improve the detection accuracy when some objects are blocked by clouds, top-hat transform is employed to split the sky into cloudy region and non-cloudy region. A multi-level thresholding algorithm is developed to select the optimal threshold for different regions. Experimental results show that our proposed approach can successfully detect the blocked objects by clouds.

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