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ImageDstcvConvertScale(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 imagecvDFT(Fourier, dst, CV_DXT_FORWARD);// Application of the forward Fourier transformcvReleaseImage(&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 + MagcvLog( image_Re, image_Re ); // log(1 + Mag)//Rearrange the quadrants of Fourier image so that the origin is at the image centernRow = 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)]*255double minVal = 0, maxVal = 0;// Localize minimum and maximum valuescvMinMaxLoc( image_Re, &minVal, &maxVal );// Normalize image (0 - 255) to be observed as an u8 imagescale = 255/(maxVal - minVal);shift = -minVal * scale;cvConvertScale(image_Re, dst, scale, shift);cvReleaseImage(&image_Re);cvReleaseImage(&image_Im);}