A Novel Wavelet Multiple Thresholding Algorithm for Astronomical Spectral Signal Denoising
ZHAO Rui-zhen1,HU Zhan-yi2,HU Shao-hai1
1. School of Computer and Information Technology,Beijing Jiaotong University,Beijing 100044,China 2. National Key Laboratory of Pattern Recognition,Institute of Automation,Chinese Academy of Sciences,Beijing 100080,China
Abstract：By using the different relativities of spectral lines and noises in the wavelet domain,a novel wavelet multiple thresholding algorithm is presented in the present paper for astronomical spectra with low signal-noise-ratio (SNR). Firstly the wavelet coefficients are estimated by NeighShrink approach and then 0-1 coefficients are obtained. Based on the above binary coefficients,two kinds of relativity exponents at each scale and across scales respectively are defined for each wavelet coefficients. Finally decision coefficients are determined according to the magnitudes of the relativity exponents. This algorithm overcomes the over-reserving or over-shrinking disadvantages of the simple threshold method in that the decision coefficients are obtained by multiple criteria. Besides,large pulse noises can be removed by the presented algorithm because it takes spectral line features into consideration. The experimental results show that the proposed algorithm is computationally efficient and practical.
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