[A method for auto-extraction of spectral lines based on sparse representation].
A new method for auto-extraction of spectral lines based on sparse representation is presented in the present paper. Firstly, the authors proposed a wavelet denoising scheme using a new theory called sparse representation for noise removal. After performing wavelet transform on the spectral signal, this method implements noise removal by solving an optimization problem, which makes the wavelet coefficients at each scale sparsest. The proposed method not only takes the structure properties in the wavelet coefficients into consideration, but also can well maintain the local characteristics of wavelet coefficients. Therefore it can effectively keep the information of featured spectral lines during the process of denoising. Secondly, the authors got satisfying continua by respectively utilizing the wavelet transform method and spline fitting method. The strong spectral lines were firstly removed from the given spectrum with wavelet transform, leading to the result that the obtained continuum approximated the real one very well. Finally, the spectrum was divided point to point by the obtainable continuum and the normalized spectrum was obtained. And then spectral lines were extracted from the normalized spectrum by using adaptive local thresholding scheme. Experimental results show that the proposed method is effective and efficient in the application of auto-extraction of spectral lines. The authors' method will be also helpful for the automatic classification of astronomical spectra.
Institute of Information Science, Beijing Jiaotong University, Beijing 100044, China. rzhzhao@bjtu.edu.cn
Rui-Zhen
RZ
Zhao
Fei
F
Wang
A-Li
AL
Luo
Yan-Xia
YX
Zhang