Combined with the characteristics of seismic image noise, using multi-scale wavelet transform, presents a new adaptive wavelet threshold denoising algorithm.
结合地震图像噪声的特点，利用多尺度小波变换的优点，提出一种新的自适应小波阈值去噪算法。
Finally, wavelet threshold de-noising method was used to analyze the experimental signal of the two systems. The results showed this method can make some de-noising effect.
最后，运用小波阈值去噪法对两个系统的实验信号进行了分析，结果表明该方法对提高信噪比，抑制噪声具有一定的作用。
The experimental results showed that compared with other common wavelet threshold desnoising methods, the presented method can improve the visual effect and increase SNR of the denoised image.
实验结果表明，与普通小波阈值去噪方法相比，该算法能获得较好的图像效果，提高信噪比。
Aiming at the disadvantages of traditional soft and hard threshold methods for wavelet threshold denoising, the new developed extracting threshold denoising method is proposed.
针对小波阈值去噪方法中传统软硬阈值法各自存在的缺点，提出了开方法阈值去噪法。
Due to different wavelet threshold fit for different characteristic of signal, various wavelet de-noise threshold was used to decline the harmonics of signal and the best threshold was chosen.
由于在小波降噪中不同的阈值适应的信号特征不同，采用多种小波阈值对城市轨道交通牵引供电系统谐波信号进行降噪，并从中选择了最优的降噪阈值，达到对信号的优化处理。
Due to different wavelet threshold fit for different characteristic of signal, various wavelet de-noise threshold was used to decline the harmonics of signal and the best threshold was chosen.
由于在小波降噪中不同的阈值适应的信号特征不同，采用多种小波阈值对城市轨道交通牵引供电系统谐波信号进行降噪，并从中选择了最优的降噪阈值，达到对信号的优化处理。
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