摘要
在Daubechies小波分解变换的基础上,研究一种自适应阈值白光干涉数据去噪方法——自适应阈值去噪方法(adapt threshold shrink,ATS)的白光干涉数据去噪方法。这种方法是基于Bayes框架,在不同子带上选择不同的最佳阈值。结合软阈值法对白光干涉信号进行去噪,与传统方法相比,此种方法提高了去噪后白光干涉数据的信噪比,而且使数据波形更加清晰。基于Daubechies小波的自适应阈值白光干涉数据去噪法实现简单、计算速度快、去噪效果好。
An adaptive threshold Based on Daubechies wavelet for data denoising of white light interference spectrum. This method is derived in a Bayesian framework and threshold is chosen according to different sub bands and orientations. Comparing with traditional denoising methods, this method combined with soft threshold algorithm, can improve the SNR more effectively and also makes denoised signal more clearly. Adaptive threshold based on Daubechies wavelet transform, which can be computed fast with a simple implementation, has a good effect for data of white light interference spectrum denoising.
出处
《国外电子测量技术》
2008年第11期20-22,32,共4页
Foreign Electronic Measurement Technology
