A Wavelet-Transform-Based Method for the Automatic Detection of Late-Type Stars
LIU Zhong-tian1, ZHAO Rui-zhen2, ZHAO Yong-heng3,WU Fu-chao1
1.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, China 2.School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China 3.National Astronomical Observatory, Chinese Academy of Sciences, Beijing 100012, China
Abstract：The LAMOST project, the world largest sky survey project, urgently needs an automatic late-type stars detection system.However, to our knowledge, no effective methods for automatic late-type stars detection have been reported in the literature up to now.The present study work is intended to explore possible ways to deal with this issue.Here, by “late-type stars" we mean those stars with strong molecule absorption bands, including oxygen-rich M, L and T type stars and carbon-rich C stars.Based on experimental results, the authors find that after a wavelet transform with 5 scales on the late-type stars spectra, their frequency spectrum of the transformed coefficient on the 5th scale consistently manifests a unimodal distribution, and the energy of frequency spectrum is largely concentrated on a small neighborhood centered around the unique peak.However, for the spectra of other celestial bodies, the corresponding frequency spectrum is of multimodal and the energy of frequency spectrum is dispersible.Based on such a finding, the authors presented a wavelet-transform-based automatic late-type stars detection method.The proposed method is shown by extensive experiments to be practical and of good robustness.
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