Rui-Lan Lü, Tie-Jun Wu, Ling Yu
Institute of Intelligent Systems and Decision-making, Zhejiang University, Hangzhou 310027, China.
Guang Pu Xue Yu Guang Pu Fen Xi. 2004 Jul;24(7):826-9.
An ideal spectrum signal prototype is constructed in this paper based on the infrared ray spectrum of octane levelmeasurement to evaluate the performances of wavelet based threshold denoising approaches via different combinations of mother wavelet functions and thresholds. A performance index eta is defined to assess the signal-to-noise ratios (SNR) of denoising results, inconsideration of the trade-off between the SNR and the distortion of the original signal after wavelet denoising. Three families of mother wavelets (Symlets, Daubechies and Coiflet), four threshold selection rules (Rigrsure, Sqtwolog, Heursure and Manimaxi), and three threshold rescaling methods (One, Sln and Mln) are tested in a series of experiments to estimate the functioning of those wavelets and thresholding parameters. Experimental results show that in the cases investigated in this paper, the best denoising performance is reached via the combinations of Daubechies9 or Symlet7, 11, 14, 15 wavelets, "Rigrsure" threshold selection rule, and "Sln" threshold rescaling method.
本文基于辛烷值测量的红外光谱构建了理想的光谱信号原型,以通过母小波函数和阈值的不同组合来评估基于小波的阈值去噪方法的性能。定义了一个性能指标eta来评估去噪结果的信噪比(SNR),同时考虑到小波去噪后SNR与原始信号失真之间的权衡。在一系列实验中测试了三类母小波(Symlets、Daubechies和Coiflet)、四种阈值选择规则(Rigrsure、Sqtwolog、Heursure和Manimaxi)以及三种阈值重缩放方法(One、Sln和Mln),以估计这些小波和阈值参数的功能。实验结果表明,在本文研究的情况下,通过Daubechies9或Symlet7、11、14、15小波、“Rigrsure”阈值选择规则和“Sln”阈值重缩放方法的组合可达到最佳去噪性能。