图像处理 之 一维快速傅里叶变换（FFT）

2019-04-15 14:03发布

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# -*- coding: utf-8 -*- """ Created on Sun Jul 8 21:05:51 2018 @author: Diko """ import numpy def FFT_v1(Img,Wr): if Img.shape[0]==2: pic = numpy.zeros([2],dtype=complex) pic = pic*(1+0j) pic[0]=Img[0]+Img[1]*Wr[0] pic[1]=Img[0]-Img[1]*Wr[0] return pic else: pic = numpy.empty([Img.shape[0]],dtype=complex) pic[0:Img.shape[0]//2] = FFT_v1(Img[::2],Wr[::2])+Wr*FFT_v1(Img[1::2],Wr[::2]) pic[Img.shape[0]//2:Img.shape[0]]=FFT_v1(Img[::2],Wr[::2])-Wr*FFT_v1(Img[1::2],Wr[::2]) return pic; def FFT_1d(Img): Wr = numpy.ones([Img.shape[0]//2])*[numpy.cos(2*numpy.pi*i/Img.shape[0])-1j*numpy.sin(2*numpy.pi*i/Img.shape[0]) for i in numpy.arange(Img.shape[0]/2)] return FFT_v1(Img,Wr)  

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