摘要
本文介绍了小波分解与重构、小波变换阈值及小波变换模极大值三种常用的小波去噪方法,并将上述三种方法分别对叠加了高斯白噪声的仿真信号进行去噪处理。对三种方法的优缺点进行了比较和分析,结果表明:对于信号和噪声的频带相互分离的含有确定性噪声的信号,选用方法简单、计算速度快的小波分解与重构去噪法最为合适;对于含有高斯白噪声的信号,可以选用阈值法和模极大值法。由于阈值法具有能得到原始信号的近似最优估计、计算速度快以及具有广泛的适应性等优点,因而成为小波去噪方法中应用最广泛的一种去噪方法。小波变换模极大值法对于信号中含有较多的奇异点的信号去噪效果最好,但其缺点是计算速度慢。在实际应用中需权衡去噪效果和计算速度之间的关系,有效、合理地选择最适合实际资料的去噪方法。
The paper introduced three common-used de-noise approaches by wavelet; wavelet decomposition and reconstruction,threshold of wavelet transform and modular extreme of wavelet transform. The denoise processing is carried out by abovementioned approaches for simulated signals adding Gauss white noise respectively,and correlation and analysis of advantages and disadvantages of these three approaches showed that it is suitable to select wavelet decomposition and reconstruction as denoise approach that is characterized by simple method and rapid computational speed when the denoise processing is carried out for the signals with band-separated signal and noise and determinable noise; the threshold and modular extreme approaches can be selected for the denoise processing of Gauss white-noise-bearing signals. Since the threshold approach is characterized by obtaining the approximate optimum evaluation of original signal,rapid computational speed and wide adaptability, which is most popular-used denoise approach among the wavelet denoise methods. The modular extreme approach of wavelet transform has better denoise effects for the signals containing more singularities, but its disadvantage is slow computational speed. It should strike a balance between the denoise effect and computational speed and effectively and reasonably select the denoise approach that is suitable for the practical data when practically using wavelet transform for denoise.
出处
《石油地球物理勘探》
EI
CSCD
北大核心
2007年第B08期118-123,共6页
Oil Geophysical Prospecting
关键词
小波变换
信噪比
去噪
阚值
模极大值
wavelet transform, S/N ratio, denoise, threshold,modular extreme
