基于卷积型小波包变换的谱线自动提取方法

天体光谱中的谱线包含重要的天体物理信息。文章提出一种基于卷积型小波包变换的谱线自动提取方法。该方法由以下主要步骤组成：(1)将观测光谱进行4层卷积型小波包变换;(2)对第四层小波包系数，采用区域相关算法以及阈值处理方法进行噪声处理;(3)选择中高频小波包系数进行谱线特征重构;(4)根据重构后的谱线特征，利用谱线搜索方法，在观测光谱中提取谱线。作者在实验中用恒星、正常星系和活动星系光谱进行谱线提取测试，结果表明该方法具有对噪声鲁棒和谱线提取准确等特点。用该方法提取sloan digital sky survey(SDSS)光谱中的谱线后，计算了红移并与SDSS给出的红移进行了对比，实验结果间接验证了该方法提取谱线的有效性。

A Method for Auto-Extraction of Spectral Lines Based on Convolution Type of Wavelet Packet Transformation

The important astrophysical information is hidden in spectral lines of astronomical spectra.The presen paper presents a method for auto-extraction of spectral lines based on convolution type of wavelet packet.This method consists of four main steps: First,the observed spectra are transformed by convolution type of wavelet packet with 4~(th) scale.Then,the noise with coefficients of the 4~(th) scale is eliminated by the local correlation algorithm and threshold in the wavelet packet domain.After that,middle and high frequency coefficients are selected to reconstruct the feature of the spectral lines.Finally,with the reconstructed feature of the spectral lines,spectral lines in observed spectra are searched.The results of our experiments,which include the spectral lines of stars,normal galaxies and active galaxies,show that the method can robustly and accurately extract the spectral lines.The method was applied to extract the SDSS spectral lines and compute the redshifts with those lines.By comparing the redshifts with those given by SDSS,the extraction has proven successful and practical.