傅利葉變換會將影象分解成其正弦和余弦分量。換句話說，它將影象從空間域轉換到頻率域。這個想法是，任何函式都可以用無限的正弦和余弦函式之和精確地近似。傅利葉變換是一種方法。數學上，二維影象的傅利葉變換為：
#include "opencv2/core.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/imgcodecs.hpp"
#include "opencv2/highgui.hpp"
#include using namespace cv;
using namespace std;
static void help(char ** ar**)
int main(int argc, char ** ar**)
mat padded; //expand input image to optimal size
int m = getoptimaldftsize( i.rows );
int n = getoptimaldftsize( i.cols ); // on the border add zero values
copymakeborder(i, padded, 0, m - i.rows, 0, n - i.cols, border_constant, scalar::all(0));
mat planes = ;
mat complexi;
merge(planes, 2, complexi); // add to the expanded another plane with zeros
dft(complexi, complexi); // this way the result may fit in the source matrix
// compute the magnitude and switch to logarithmic scale
// => log(1 + sqrt(re(dft(i))^2 + im(dft(i))^2))
split(complexi, planes); // planes[0] = re(dft(i), planes[1] = im(dft(i))
magnitude(planes[0], planes[1], planes[0]);// planes[0] = magnitude
mat magi = planes[0];
magi += scalar::all(1); // switch to logarithmic scale
log(magi, magi);
// crop the spectrum, if it has an odd number of rows or columns
magi = magi(rect(0, 0, magi.cols & -2, magi.rows & -2));
// rearrange the quadrants of fourier image so that the origin is at the image center
int cx = magi.cols/2;
int cy = magi.rows/2;
mat q0(magi, rect(0, 0, cx, cy)); // top-left - create a roi per quadrant
mat q1(magi, rect(cx, 0, cx, cy)); // top-right
mat q2(magi, rect(0, cy, cx, cy)); // bottom-left
mat q3(magi, rect(cx, cy, cx, cy)); // bottom-right
mat tmp; // swap quadrants (top-left with bottom-right)
q0.copyto(tmp);
q3.copyto(q0);
tmp.copyto(q3);
q1.copyto(tmp); // swap quadrant (top-right with bottom-left)
q2.copyto(q1);
tmp.copyto(q2);
normalize(magi, magi, 0, 1, norm_minmax); // transform the matrix with float values into a
// viewable image form (float between values 0 and 1).
imshow("input image" , i ); // show the result
imshow("spectrum magnitude", magi);
waitkey();
return exit_success;
}
mat padded; //expand input image to optimal size
int m = getoptimaldftsize( i.rows );
int n = getoptimaldftsize( i.cols ); // on the border add zero values
copymakeborder(i, padded, 0, m - i.rows, 0, n - i.cols, border_constant, scalar::all(0));
mat planes = ;
mat complexi;
merge(planes, 2, complexi); // add to the expanded another plane with zeros
dft(complexi, complexi); // this way the result may fit in the source matrixsplit(complexi, planes); // planes[0] = re(dft(i), planes[1] = im(dft(i))
magnitude(planes[0], planes[1], planes[0]);// planes[0] = magnitude
mat magi = planes[0];
magi += scalar::all(1); // switch to logarithmic scale
log(magi, magi);
// crop the spectrum, if it has an odd number of rows or columns
magi = magi(rect(0, 0, magi.cols & -2, magi.rows & -2));
// rearrange the quadrants of fourier image so that the origin is at the image center
int cx = magi.cols/2;
int cy = magi.rows/2;
mat q0(magi, rect(0, 0, cx, cy)); // top-left - create a roi per quadrant
mat q1(magi, rect(cx, 0, cx, cy)); // top-right
mat q2(magi, rect(0, cy, cx, cy)); // bottom-left
mat q3(magi, rect(cx, cy, cx, cy)); // bottom-right
mat tmp; // swap quadrants (top-left with bottom-right)
q0.copyto(tmp);
q3.copyto(q0);
tmp.copyto(q3);
q1.copyto(tmp); // swap quadrant (top-right with bottom-left)
q2.copyto(q1);
tmp.copyto(q2);
normalize(magi, magi, 0, 1, norm_minmax); // transform the matrix with float values into a
// viewable image form (float between values 0 and 1).
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