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小波理论是傅里叶分析这一学科半个世纪以来的工作结晶，已成功应用于信号分析、图像处理及非线性科学等方面。本文基于小波变换可提取信号所需频率成分的特性，提出了小波变换频谱细化方法，文中介绍了小波变换频谱细化的原理和步骤，进行了计算验证，并与复调制ZOOM－FFT方法进行了比较，结果表明，小波变换细化谱方法，可得到比复调制ZOOM—FFT方法更细密的结果，小波变换细化谱方法实现起来更简单、容易，但计算量较大。
Wavelet theory is the crystallization of the work of Fourier analysis since the last half a century and has been successfully applied in signal analysis, image processing and nonlinear science. Based on the characteristics of the frequency components that can be extracted by wavelet transform, this paper presents a spectral refinement method based on wavelet transform. The principle and steps of spectral refinement of wavelet transform are introduced in this paper. The calculation and verification are carried out and compared with the ZOOM-FFT method The results show that the wavelet transform refinement spectrum method can get finer results than the ZOOM-FFT method. The wavelet transform refinement spectrum method is simpler and easier to implement, but more computationally intensive.