Automatically determining redshifts of galaxies is very important for astronomical research on large samples, such as large-scale structure of cosmological significance. Galaxies are generally divided into normal galaxies and active galaxies, and the spectra of active galaxies mostly have more obvious emission lines. In the present paper, the authors present a novel method to determine spectral redshifts of active galaxies rapidly based on wavelet transformation mainly, and it does not need to extract line information accurately. This method includes the following steps; Firstly, we denoised a spectrum to be processed; Secondly, the low-frequency spectrum was extracted based on wavelet transform, and then we could get the residual spectrum through the denoised spectrum subtracting the low-frequency spectrum; Thirdly, the authors calculated the standard deviation of the residual spectrum and determined a threshold value T, then retained the wavelength set whose corresponding flux was greater than T; Fourthly, according to the wavelength form of all the standard lines, we calculated all the candidate redshifts; Finally, utilizing the density estimation method based on Parzen window, we determined the redshift point with maximum density, and the average value of its neighborhood would be the final redshift of this spectrum. The experiments on simulated data and real data from SDSS-DR7 show that this method is robust and its correct rate is encouraging. And it can be expected to be applied in the project of LAMOST.%星系红移的自动测量对进行大样本天文学研究如宇宙学大尺度结构研究具有重要意义.星系一般分为正常星系和活动星系两种,活动星系光谱一般具有较明显的发射线特征.文章提出了一种不用精确提取谱线而快速测量活动星系光谱红移的方法.该方法包括步骤:(1)对待测光谱进行去噪；(2)利用小波变换提取低频成分光谱,并用去噪后光谱减去低频谱得到残差谱；(3)计算残差谱的均方差,并保留大于阈值的波长集合(4)根据标准谱线表计算所有候选红移；(5)利用Parzen窗估计方法计算红移密度最大点,并在邻域内求均值确定最终红移.对模拟数据和SDSS DR7部分实测数据的测试表明,该方法是鲁棒的并且具有较高的红移测量正确率.
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