[人工智能]图像功率谱

功率谱如图：
(C++实现)
（MATLAB实现）

代码：
C++：

#include<opencv2\core.hpp>
#include<opencv2\imgproc.hpp>
#include<opencv2\imgcodecs.hpp>
#include<opencv2\highgui.hpp>
#include<iostream>

using namespace cv;
using namespace std;

void ShiftDFT(Mat img);

int main(int argc, char ** argv)
{
	Mat I = imread("Lena.jpg");
	if (I.empty())
	{
		cout << "Error opening image" << endl;
		return EXIT_FAILURE;
	}
	Mat padded;            //expand input image to optimal size
	int m = getOptimalDFTSize(I.rows);
	int n = getOptimalDFTSize(I.cols);
	copyMakeBorder(I,padded,0,m-I.rows,0,n-I.cols,BORDER_CONSTANT,Scalar::all(0));

	Mat planes[] = {Mat_<float>(padded),Mat::zeros(padded.size(),CV_32F)};
	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

	split(complexI,planes);	// planes[0] = Re(DFT(I), planes[1] = Im(DFT(I))
	Mat Re = planes[0];
	Mat Im = planes[1];
	
	//计算功率谱
	Mat P;
	P = Re*Re + Im*Im;
	P += Scalar::all(1);
	log(P, P);	//switch to logarithmic scale

	ShiftDFT(P);
	normalize(P,P,0,1,NORM_MINMAX);//Transform the matrix with float values into a
	                              //viewable image form (float between values 0 and 1).
	imshow("spectrum power",P);
	waitKey();
	
	return EXIT_SUCCESS;
}

void ShiftDFT(Mat img)
{
	int cx = img.cols / 2;
	int cy = img.rows / 2;

	Mat q0(img, Rect(0, 0, cx, cy));
	Mat q1(img, Rect(cx, 0, cx, cy));
	Mat q2(img, Rect(0, cy, cx, cy));
	Mat q3(img, Rect(cx, cy, cx, cy));

	Mat tmp;
	q0.copyTo(tmp);
	q3.copyTo(q0);
	tmp.copyTo(q3);

	q1.copyTo(tmp);
	q2.copyTo(q1);
	tmp.copyTo(q2);
}

MATLAB：

f=imread("Lena.jpg");
F=fft2(f);
Re=real(F);
Im=imag(F);
Psd=Re.*Re+Im.*Im;
Psd=fftshift(log(1+abs(Psd)));
Psd=mat2gray(Psd,[min(Psd(:)),max(Psd(:))]);
figure;
imshow(Psd);