static ComplexNumber* Dft2(MyImage const &Scr);

ComplexNumber* MyCV::Dft2(MyImage const &Scr){int width = Scr.m_width;int height = Scr.m_height;// 将 scr_data 转化为灰度
MyImage *grayimage = Gray(Scr);unsigned char* gray_data = grayimage->m_data;int gray_bytesPerLine = grayimage->m_bytesPerLine;// 将 gray_data 转化为 double 型，并去掉用于填充的多余空间double *double_data = new double[width*height];for(int i=0;i<height;i++)for(int j=0;j<width;j++){double_data[i*width+j]=(double)gray_data[i*gray_bytesPerLine+j];}// 对 double_data 进行傅里叶变换
ComplexNumber *dft2_data = new ComplexNumber[width*height];double fixed_factor_for_axisX = (-2 * PI) / height;// evaluate -i2π/N of -i2πux/N, and store the value for computing efficiencydouble fixed_factor_for_axisY = (-2 * PI) / width;// evaluate -i2π/N of -i2πux/N, and store the value for computing efficiencyfor (int u = 0; u<height; u++) {for (int v = 0; v<width; v++) {for (int x = 0; x<height; x++) {for (int y = 0; y<width; y++) {double powerX = u * x * fixed_factor_for_axisX; // evaluate -i2πux/Ndouble powerY = v * y * fixed_factor_for_axisY; // evaluate -i2πux/N
ComplexNumber cplTemp;cplTemp.m_rl = double_data[y + x*width] * cos(powerX + powerY);// evaluate f(x) * e^(-i2πux/N), which is equal to f(x) * (cos(-i2πux/N)+sin(-i2πux/N)i) according to Euler's formula
cplTemp.m_im = double_data[y + x*width] * sin(powerX + powerY);dft2_data[v + u*width] = dft2_data[v + u*width] + cplTemp;}}}}// 返回傅里叶数组return dft2_data;}

static MyImage* Dft22MyImage(ComplexNumber *Scr,int width,int height);

MyImage* MyCV::Dft22MyImage(ComplexNumber *Scr, int const width, int const height){// 将傅里叶数组归一化// 取模double mold[width*height];for(int i = 0 ;i<width*height;i++){mold[i] = Scr[i].get_mold();}// 获取最小值double min = mold[0];for(int i = 0;i<width*height;i++){if(mold[i]<min)min = mold[i];}// 获取去掉前几大值的最大值double maxqueue[20] = {0.,0.,0.,0.,0.,0.,0.,0.,0.,0.,0.,0.,0.,0.,0.,0.,0.,0.,0.,0.},max;for(int i = 0;i<width*height;i++){if(mold[i]>maxqueue[0])maxqueue[0] = mold[i];}for(int j =1;j<20;j++){for(int i = 0;i<width*height;i++){if(mold[i]>maxqueue[j]&&mold[i]<maxqueue[j-1])maxqueue[j] = mold[i];}}max = maxqueue[19];unsigned char *normalized_data = new unsigned char[width*height];for(int i=0;i<height;i++)for(int j=0;j<width;j++){unsigned char t = (unsigned char)((mold[i*width+j]-min)/(max-min)*255);if(t>255)t = 255;normalized_data[i*width+j]=t;}// 将图像中心化
unsigned char* center_data = new unsigned char[width*height];for (int u = 0; u<height; u++){for (int v = 0; v<width; v++) {if ((u<(height / 2)) && (v<(width / 2))) {center_data[v + u*width] =normalized_data[width / 2 + v + (height / 2 + u)*width];}else if ((u<(height / 2)) && (v >= (width / 2))) {center_data[v + u*width] =normalized_data[(v - width / 2) + (height / 2 + u)*width];}else if ((u >= (height / 2)) && (v<(width / 2))) {center_data[v + u*width] =normalized_data[(width / 2 + v) + (u - height / 2)*width];}else if ((u >= (height / 2)) && (v >= (width / 2))) {center_data[v + u*width] =normalized_data[(v - width / 2) + (u - height / 2)*width];}}}// 向中心化的数组填充空间int bytesPerLine = (width*8+31)/32*4;unsigned char *dst_data = new unsigned char[bytesPerLine*height];for(int i=0;i<height;i++)for(int j=0;j<width;j++){dst_data[i*bytesPerLine+j] = center_data[i*width+j];}return new MyImage(dst_data,width,height,MyImage::format::GRAY8);}