openCV-傅里叶变换

从别人那里复制过来的程序

// test.cpp : 定义控制台应用程序的入口点。
//

#include "StdAfx.h"



#include <opencv2/opencv.hpp>
#include <opencv2/core/core.hpp>
#include <opencv2/features2d/features2d.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/legacy/legacy.hpp>
#include <iostream>
#include <cmath>
#include <vector>
#include <cxcore.h>



using namespace cv;
using namespace std;

void fft2(IplImage *src, IplImage *dst);
void fft2shift(IplImage *src, IplImage *dst);
int main(int argc, char ** argv)
{
IplImage *src;          //源图像
IplImage *Fourier;   //傅里叶系数
IplImage *dst ;


IplImage *ImageRe;
IplImage *ImageIm;
IplImage *ImageIm1;

IplImage *Image;
IplImage *ImageDst;


double m,M;
double scale;
double shift;
src = cvLoadImage("lena.bmp",0);   //加载源图像，第二个参数表示将输入的图片转为单信道 
Fourier = cvCreateImage(cvGetSize(src),IPL_DEPTH_64F,2);
dst = cvCreateImage(cvGetSize(src),IPL_DEPTH_64F,2);
ImageRe = cvCreateImage(cvGetSize(src),IPL_DEPTH_64F,1);
ImageIm = cvCreateImage(cvGetSize(src),IPL_DEPTH_64F,1);
ImageIm1 = cvCreateImage(cvGetSize(src),IPL_DEPTH_64F,1);
Image = cvCreateImage(cvGetSize(src),src->depth,src->nChannels);
ImageDst = cvCreateImage(cvGetSize(src),src->depth,src->nChannels);
fft2(src,Fourier);                  //傅里叶变换
fft2shift(Fourier, Image);          //中心化
cvDFT(Fourier,dst,CV_DXT_INV_SCALE);//实现傅里叶逆变换，并对结果进行缩放

cvSplit(dst,ImageRe,ImageIm,0,0);


cvNamedWindow("源图像",0);
cvShowImage("源图像",src);             
//对数组每个元素平方并存储在第二个参数中
cvPow(ImageRe,ImageRe,2);               
cvPow(ImageIm,ImageIm1,2);
cvAdd(ImageRe,ImageIm1,ImageRe,NULL);
cvPow(ImageRe,ImageRe,0.5);
cvMinMaxLoc(ImageRe,&m,&M,NULL,NULL);
scale = 255/(M - m);
shift = -m * scale;
//将shift加在ImageRe各元素按比例缩放的结果上，存储为ImageDst
cvConvertScale(ImageRe,ImageDst,scale,shift);


cvNormalize(ImageIm,ImageIm, 0, 1, CV_MINMAX);
cvNamedWindow("傅里叶谱",0);
cvShowImage("傅里叶谱",Image);
cvNamedWindow("傅里叶逆变换",0);
cvShowImage("傅里叶逆变换",ImageDst);
cvNamedWindow("test",0);
cvShowImage("test",ImageIm);

cvWaitKey(0);


cvReleaseImage(&src);
cvReleaseImage(&Image);
cvReleaseImage(&ImageIm);
cvReleaseImage(&ImageRe);
cvReleaseImage(&Fourier);
cvReleaseImage(&dst);
cvReleaseImage(&ImageDst);
        cvDestroyAllWindows();
return 0;

    return 0;
}

void fft2(IplImage *src, IplImage *dst)
{  
IplImage *image_Re = 0, *image_Im = 0, *Fourier = 0; //实部、虚部


image_Re = cvCreateImage(cvGetSize(src), IPL_DEPTH_64F, 1);  //实部


image_Im = cvCreateImage(cvGetSize(src), IPL_DEPTH_64F, 1);  //虚部


Fourier = cvCreateImage(cvGetSize(src), IPL_DEPTH_64F, 2);//2 channels (image_Re, image_Im)


cvConvertScale(src, image_Re, 1, 0);// Real part conversion from u8 to 64f (double)


cvZero(image_Im);// Imaginary part (zeros)


cvMerge(image_Re, image_Im, 0, 0, Fourier);// Join real and imaginary parts and stock them in Fourier image


cvDFT(Fourier, dst, CV_DXT_FORWARD);// Application of the forward Fourier transform


cvReleaseImage(&image_Re);
cvReleaseImage(&image_Im);
cvReleaseImage(&Fourier);
}
void fft2shift(IplImage *src, IplImage *dst)
{
IplImage *image_Re = 0, *image_Im = 0;
int nRow, nCol, i, j, cy, cx;
double scale, shift, tmp13, tmp24;


image_Re = cvCreateImage(cvGetSize(src), IPL_DEPTH_64F, 1);


image_Im = cvCreateImage(cvGetSize(src), IPL_DEPTH_64F, 1);
cvSplit( src, image_Re, image_Im, 0, 0 );


//具体原理见冈萨雷斯数字图像处理p123
// Compute the magnitude of the spectrum Mag = sqrt(Re^2 + Im^2)
//计算傅里叶谱
cvPow( image_Re, image_Re, 2.0);
cvPow( image_Im, image_Im, 2.0);
cvAdd( image_Re, image_Im, image_Re);
cvPow( image_Re, image_Re, 0.5 );


//对数变换以增强灰度级细节(这种变换使以窄带低灰度输入图像值映射一宽带输出值，具体可见冈萨雷斯数字图像处理p62)
// Compute log(1 + Mag);
cvAddS( image_Re, cvScalar(1.0), image_Re ); // 1 + Mag
cvLog( image_Re, image_Re ); // log(1 + Mag)


//Rearrange the quadrants of Fourier image so that the origin is at the image center
nRow = src->height; nCol = src->width;
cx = nCol/2; cy = nRow/2; // image center


//CV_IMAGE_ELEM为OpenCV定义的宏，用来读取图像的像素值，这一部分就是进行中心变换
for( j = 0; j < cy; j++ ){
for( i = 0; i < cx; i++ ){
//中心化，将整体份成四块进行对角交换
tmp13 = CV_IMAGE_ELEM( image_Re, double, j, i);
CV_IMAGE_ELEM( image_Re, double, j, i) = CV_IMAGE_ELEM(image_Re, double, j+cy, i+cx);
CV_IMAGE_ELEM( image_Re, double, j+cy, i+cx) = tmp13;


tmp24 = CV_IMAGE_ELEM( image_Re, double, j, i+cx);
CV_IMAGE_ELEM( image_Re, double, j, i+cx) =CV_IMAGE_ELEM( image_Re, double, j+cy, i);
CV_IMAGE_ELEM( image_Re, double, j+cy, i) = tmp24;
}
}
//归一化处理将矩阵的元素值归一为[0,255]
//[(f(x,y)-minVal)/(maxVal-minVal)]*255
double minVal = 0, maxVal = 0;
// Localize minimum and maximum values
cvMinMaxLoc( image_Re, &minVal, &maxVal );
// Normalize image (0 - 255) to be observed as an u8 image
scale = 255/(maxVal - minVal);
shift = -minVal * scale;
cvConvertScale(image_Re, dst, scale, shift);
cvReleaseImage(&image_Re);
cvReleaseImage(&image_Im);


}