表面技术2016，Vol.45Issue(5)：229-234,6.DOI:10.16490/j.cnki.issn.1001-3660.2016.05.036
小波变换在薄膜表面图像信号降噪中的应用
Application of Wavelet Transform in the Signal Noise Reduction of Film Surface Images
摘要
Abstract
ABSTRACT:Objective The surface images of nano-scale thin film samples can be obtained by the scanning probe micro-scope device represented by atomic force microscope, but these images have different degrees of noise, which affect the quality of the image and the judgment of image information. In order to obtain the surface state of the film more accurately, noise re-duction of the surface image data and information of the sample is needed.Methods This paper proposed a multi-layer wavelet decomposition noise reduction algorithm based on the introduction of the basic theory of wavelet transform and the analysis of noise sources by combining the imaging characteristics of equipment such as AFM and the time-frequency locality characteris-tics of wavelet transform. Fourier transform is the basis of the traditional theory of signal, but it has some limitations as a kind of global change. Fourier transform fails to simultaneously describe the local characteristics of the time domain and the frequency domain, which are the key parts of unstable signal characteristics. The wavelet transform kept the advantage of window Fourier transforms in localization and changed its defect of fixed size.Results The frequency of the original image signal was distri-buted in the range of 0~4000 Hz. After the wavelet transform, the signal waveform was more smooth, and the frequency spec-trum was distributed between 500 Hz and 2000 Hz.Conclusion The wavelet transform was applied to signal noise reduction of the film surface images, and the experiment proved that the noise could be effectively removed using wavelet transform.关键词
小波变换/信号降噪/频谱分析Key words
wavelet transform/signal denoising/spectrum analysis分类
矿业与冶金引用本文复制引用
张伟科..小波变换在薄膜表面图像信号降噪中的应用[J].表面技术,2016,45(5):229-234,6.基金项目
辽宁省科学计划计划项目（2012217005）；辽宁省科学事业公益研究基金（2012004002）FundSupported by Liaoning Province Science Plan Project (No.2012217005) and Liaoning Province Science Public Research Fund (No.2012004002) （No.2012217005）
