图像处理FFT IFFT

#include <stdio.h> #include <cv.h> #include <cxcore.h> #include <highgui.h> double minVal = 0, maxVal = 0; // Localize minimum and maximum values //傅里叶正变换 void fft2(IplImage *src, IplImage *dst) { //实部、虚部 IplImage *image_Re = 0, *image_Im = 0, *Fourier = 0; // int i, j; image_Re = cvCreateImage(cvGetSize(src), IPL_DEPTH_64F, 1); //实部 //Imaginary part image_Im = cvCreateImage(cvGetSize(src), IPL_DEPTH_64F, 1); //虚部 //2 channels (image_Re, image_Im) Fourier = cvCreateImage(cvGetSize(src), IPL_DEPTH_64F, 2); // Real part conversion from u8 to 64f (double) cvConvertScale(src, image_Re, 1, 0); // Imaginary part (zeros) cvZero(image_Im); // Join real and imaginary parts and stock them in Fourier image cvMerge(image_Re, image_Im, 0, 0, Fourier); // Application of the forward Fourier transform cvDFT(Fourier, dst, CV_DXT_FORWARD,0); 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); //Imaginary part 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,NULL); 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(1.0,0,0,0), image_Re,NULL ); // 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; cy = nRow/2; // image center cx = nCol/2; //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 cvMinMaxLoc( image_Re, &minVal, &maxVal,NULL,NULL,NULL ); // 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); } int main() { IplImage *src; //源图像 IplImage *Fourier; //傅里叶系数 IplImage *dst ; IplImage *ImageRe; IplImage *ImageIm; IplImage *Image; IplImage *ImageDst; double m,M; double scale; double shift; src = cvLoadImage("1.jpg",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); 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,0);//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); cvMoveWindow("源图像",0,0); //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,ImageIm,2); cvAdd(ImageRe,ImageIm,ImageRe,NULL); cvPow(ImageRe,ImageRe,0.5); cvMinMaxLoc(ImageRe,&m,&M,NULL,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); 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); //释放图像 cvWaitKey(0); cvReleaseImage(&src); cvReleaseImage(&Image); cvReleaseImage(&ImageIm); cvReleaseImage(&ImageRe); cvReleaseImage(&Fourier); cvReleaseImage(&dst); cvReleaseImage(&ImageDst); return 0; }