opencv 中 傅里叶变换 FFT

分享一下我老师大神的人工智能教程!零基础,通俗易懂!http://blog.csdn.net/jiangjunshow

也欢迎大家转载本篇文章。分享知识,造福人民,实现我们中华民族伟大复兴!

               
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); // 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); cvReleaseImage(&image_Re); cvReleaseImage(&image_Im); cvReleaseImage(&Fourier);}void fft2shift(IplImage *src, IplImage *dst){ IplImage *image_Re = 0, *image_Im = 0int 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); 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; 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 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);}void CCVMFCView::OnFuliyeTransform(){ IplImage *src; 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 = workImg; if(workImg->nChannels==3)  OnColorToGray(); src=cvCreateImage(cvGetSize(workImg),IPL_DEPTH_64F,workImg->nChannels);  //源图像 imageClone(workImg,&src); cvFlip(src); 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);//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,ImageIm,2); cvAdd(ImageRe,ImageIm,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); 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(10000); cvReleaseImage(&src); cvReleaseImage(&Image); cvReleaseImage(&ImageIm); cvReleaseImage(&ImageRe); cvReleaseImage(&Fourier); cvReleaseImage(&dst); cvReleaseImage(&ImageDst); Invalidate();}

           

给我老师的人工智能教程打call!http://blog.csdn.net/jiangjunshow

这里写图片描述

猜你喜欢

转载自blog.csdn.net/kahncc/article/details/83939231