int main(int argc, char ** argv)
{
const char* filename = argc >=2 ? argv[1] : "lena.jpg";
IplImage * im;
IplImage * realInput;
IplImage * imaginaryInput;
IplImage * complexInput;
int dft_M, dft_N;
CvMat* dft_A, tmp;
IplImage * image_Re;
IplImage * image_Im;
double m, M;
im = cvLoadImage( filename, CV_LOAD_IMAGE_GRAYSCALE );
if( !im )
return -1;
realInput = cvCreateImage( cvGetSize(im), IPL_DEPTH_64F, 1);
imaginaryInput = cvCreateImage( cvGetSize(im), IPL_DEPTH_64F, 1);
complexInput = cvCreateImage( cvGetSize(im), IPL_DEPTH_64F, 2);
cvScale(im, realInput, 1.0, 0.0);
cvZero(imaginaryInput);
cvMerge(realInput, imaginaryInput, NULL, NULL, complexInput);
dft_M = cvGetOptimalDFTSize( im->height - 1 );
dft_N = cvGetOptimalDFTSize( im->width - 1 );
dft_A = cvCreateMat( dft_M, dft_N, CV_64FC2 );
image_Re = cvCreateImage( cvSize(dft_N, dft_M), IPL_DEPTH_64F, 1);
image_Im = cvCreateImage( cvSize(dft_N, dft_M), IPL_DEPTH_64F, 1);
// copy A to dft_A and pad dft_A with zeros
cvGetSubRect( dft_A, &tmp, cvRect(0,0, im->width, im->height));
cvCopy( complexInput, &tmp, NULL );
if( dft_A->cols > im->width )
{
cvGetSubRect( dft_A, &tmp, cvRect(im->width,0, dft_A->cols - im->width, im->height));
cvZero( &tmp );
}
// no need to pad bottom part of dft_A with zeros because of
// use nonzero_rows parameter in cvDFT() call below
cvDFT( dft_A, dft_A, CV_DXT_FORWARD, complexInput->height );
cvNamedWindow("win", 0);
cvNamedWindow("magnitude", 0);
cvShowImage("win", im);
// Split Fourier in real and imaginary parts
cvSplit( dft_A, image_Re, image_Im, 0, 0 );
// Compute the magnitude of the spectrum Mag = sqrt(Re^2 + Im^2)
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 );
// Compute log(1 + Mag)
cvAddS( image_Re, cvScalarAll(1.0), 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
cvShiftDFT( image_Re, image_Re );
cvMinMaxLoc(image_Re, &m, &M, NULL, NULL, NULL);
cvScale(image_Re, image_Re, 1.0/(M-m), 1.0*(-m)/(M-m));
cvShowImage("magnitude", image_Re);
cvWaitKey(-1);
return 0;
}
void CMagicCabsineUniversalProperty_feature_texture_spectral_DFT::ComputeProperty()
{
IplImage * im;//输入图像必须是灰度图像
IplImage * realInput;
IplImage * imaginaryInput;
IplImage * complexInput;
int dft_M, dft_N;
CvMat* dft_A, tmp;
IplImage * image_Im;
IplImage * image_Re;
double m, M;
//灰度图转化
IplImage *srcimg_cvt = cvCreateImage(cvGetSize(srcImage),IPL_DEPTH_8U,3);//源图像格式化图像
im = cvCreateImage(cvGetSize(srcImage),IPL_DEPTH_8U,1);
cvConvertScale(srcImage,srcimg_cvt);//源图像格式化 转换成 IPL_DEPTH_32F 3通道
cvCvtColor(srcImage,im,CV_BGR2GRAY);//源图像转换成灰度图
cvReleaseImage(&srcimg_cvt);
realInput = cvCreateImage( cvGetSize(srcImage), IPL_DEPTH_64F, 1);//灰度图像
imaginaryInput = cvCreateImage( cvGetSize(srcImage), IPL_DEPTH_64F, 1);//灰度图像
complexInput = cvCreateImage( cvGetSize(srcImage), IPL_DEPTH_64F, 2);
cvScale(im, realInput, 1.0, 0.0);//从8u转换成32f 提高精度
cvZero(imaginaryInput);
//将单通道图像合并成多通道图像（将realInput和imageinaryImput合并到双通道图像complexInput）
cvMerge(realInput, imaginaryInput, NULL, NULL, complexInput);
/*dft_M = cvGetOptimalDFTSize( im->height - 1 );
dft_N = cvGetOptimalDFTSize( im->width - 1 );*/
dft_M = im->height;
dft_N = im->width;
dft_A = cvCreateMat( dft_M, dft_N, CV_64FC2 );
image_Re = cvCreateImage( cvSize(dft_N, dft_M), IPL_DEPTH_64F, 1);//DFT最佳尺寸的图像
image_Im = cvCreateImage( cvSize(dft_N, dft_M), IPL_DEPTH_64F, 1);
// copy A to dft_A and pad dft_A with zeros
cvGetSubRect( dft_A, &tmp, cvRect(0,0, im->width, im->height));
cvCopy( complexInput, &tmp, NULL );
if( dft_A->cols > im->width )
{
cvGetSubRect( dft_A, &tmp, cvRect(im->width,0, dft_A->cols - im->width, im->height));
cvZero( &tmp );
}
// no need to pad bottom part of dft_A with zeros because of
// use nonzero_rows parameter in cvDFT() call below
cvDFT( dft_A, dft_A, CV_DXT_FORWARD, complexInput->height );
// Split Fourier in real and imaginary parts
cvSplit( dft_A, image_Re, image_Im, 0, 0 );
// Compute the magnitude of the spectrum Mag = sqrt(Re^2 + Im^2)
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 );
// Compute log(1 + Mag)
cvAddS( image_Re, cvScalarAll(1.0), 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
cvShiftDFT( image_Re, image_Re );
cvMinMaxLoc(image_Re, &m, &M, NULL, NULL, NULL);
cvScale(image_Re, image_Re, 1.0/(M-m), 1.0*(-m)/(M-m));
//cvShowImage("magnitude", image_Re);
//正规化傅里叶变换图像使其可以被存储
image_Re_save = cvCreateImage(cvSize(dft_N,dft_M),IPL_DEPTH_64F,1);//注意本来应该在初始化中创建，但是由于大小参数无法估计故在此创建需要在析构函数中release
cvNormalize(image_Re,image_Re_save,255,0,CV_MINMAX,NULL);
cvReleaseImage(&im);
cvReleaseImage(&realInput);
cvReleaseImage(&imaginaryInput);
cvReleaseImage(&complexInput);
cvReleaseImage(&image_Re);
cvReleaseImage(&image_Im);
////对傅里叶进行正规化使用L2(欧几里得)范式获取正规化傅里叶系数NFP,以计算3个傅里叶系数,未加绝对值
//cvNormalize(image_Re,image_Re,1,0,CV_L2,NULL);
////test
//cvMinMaxLoc(image_Re, &m, &M, NULL, NULL, NULL);
////对傅里叶NFP取绝对值
//cvAbs(image_Re,image_Re);
////test
//cvMinMaxLoc(image_Re, &m, &M, NULL, NULL, NULL);
////计算傅里叶系数熵
//double h = FT_Entropy(image_Re, dft_N, dft_M);
//double e = FT_Energy(image_Re, dft_N, dft_M);
//double i = FT_Inertia(image_Re, dft_N, dft_M);
////存储特征
//featurefilename+=".txt";
//
//FILE* file = fopen(featurefilename.c_str(),"w");
//fprintf_s(file,"%.6f\n",h);
//fprintf_s(file,"%.6f\n",e);
//fprintf_s(file,"%.6f\n",i);
//fclose(file);
//return 0;
}
IplImage*
create_fourier_image(const IplImage *im)
{
IplImage *realInput;
IplImage *imaginaryInput;
IplImage *complexInput;
int dft_M, dft_N;
CvMat *dft_A, tmp;
IplImage *image_Re;
IplImage *image_Im;
realInput = rb_cvCreateImage( cvGetSize(im), IPL_DEPTH_64F, 1);
imaginaryInput = rb_cvCreateImage( cvGetSize(im), IPL_DEPTH_64F, 1);
complexInput = rb_cvCreateImage( cvGetSize(im), IPL_DEPTH_64F, 2);
cvScale(im, realInput, 1.0, 0.0);
cvZero(imaginaryInput);
cvMerge(realInput, imaginaryInput, NULL, NULL, complexInput);
dft_M = cvGetOptimalDFTSize( im->height - 1 );
dft_N = cvGetOptimalDFTSize( im->width - 1 );
dft_A = rb_cvCreateMat( dft_M, dft_N, CV_64FC2 );
image_Re = rb_cvCreateImage( cvSize(dft_N, dft_M), IPL_DEPTH_64F, 1);
image_Im = rb_cvCreateImage( cvSize(dft_N, dft_M), IPL_DEPTH_64F, 1);
// copy A to dft_A and pad dft_A with zeros
cvGetSubRect( dft_A, &tmp, cvRect(0,0, im->width, im->height));
cvCopy( complexInput, &tmp, NULL );
if( dft_A->cols > im->width )
{
cvGetSubRect( dft_A, &tmp, cvRect(im->width,0, dft_A->cols - im->width, im->height));
cvZero( &tmp );
}
// no need to pad bottom part of dft_A with zeros because of
// use nonzero_rows parameter in cvDFT() call below
cvDFT( dft_A, dft_A, CV_DXT_FORWARD, complexInput->height );
// Split Fourier in real and imaginary parts
cvSplit( dft_A, image_Re, image_Im, 0, 0 );
// Compute the magnitude of the spectrum Mag = sqrt(Re^2 + Im^2)
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 );
// Compute log(1 + Mag)
cvAddS( image_Re, cvScalarAll(1.0), 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
cvShiftDFT( image_Re, image_Re );
cvReleaseImage(&realInput);
cvReleaseImage(&imaginaryInput);
cvReleaseImage(&complexInput);
cvReleaseImage(&image_Im);
cvReleaseMat(&dft_A);
return image_Re;
}
void CLightSet::RunLightPrep(IplImage* src,IplImage* dest)
{
int M,N;
M=0;
N=0;
if (src->roi)
{
M = src->roi->width;
N = src->roi->height;
}
else
{
M = src->width;
N = src->height;
}
CvMat *matD; // create mat for meshgrid frequency matrices
matD = cvCreateMat(M,N,CV_32FC1);
CDM(M,N,matD);
CvMat *matH;
matH = cvCreateMat(M,N,CV_32FC1); // mat for lowpass filter
float D0 = 10.0;
float rH,rL,c;
rH = 2.0;
rL = 0.5;
c = 1.0;
lpfilter(matD,matH,D0,rH,rL,c);
IplImage *srcshift; // shift center
srcshift = cvCloneImage(src);
cvShiftDFT(srcshift,srcshift);
IplImage *log, *temp;
log = cvCreateImage(cvGetSize(src),IPL_DEPTH_32F,1);
temp = cvCreateImage(cvGetSize(src),IPL_DEPTH_32F,1);
cvCvtScale(srcshift,temp,1.0,0);
cvLog(temp,log);
cvCvtScale(log,log,-1.0,0);
CvMat *Fourier;
Fourier = cvCreateMat( M, N, CV_32FC2 );
fft2(log,Fourier);
IplImage* image_im;
image_im = cvCreateImage(cvGetSize(src),IPL_DEPTH_32F,1);
cvSplit(Fourier,dest,image_im,0,0);
cvMul(dest,matH,dest);
cvMul(image_im,matH,image_im);
IplImage *dst;
dst = cvCreateImage(cvGetSize(src),IPL_DEPTH_32F,2);
cvMerge(dest,image_im,0,0,dst);
cvDFT(dst,dst,CV_DXT_INV_SCALE);
cvExp(dst,dst);
cvZero(dest);
cvZero(image_im);
cvSplit(dst,dest,image_im,0,0);
//使得图像按照原来的顺序显示
cvShiftDFT(dest,dest);
double max,min; // normalize
cvMinMaxLoc(dest,&min,&max,NULL,NULL);
cvReleaseImage(&image_im);
cvReleaseImage(&srcshift);
cvReleaseImage(&dst);
cvReleaseImage(&log);
cvReleaseImage(&temp);
cvReleaseMat(&matD);
cvReleaseMat(&matH);
}
