【OpenCV】图像相似度检测

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#include "stdafx.h"


#include <iostream>  
#include <opencv2/opencv.hpp>
#include <opencv2/core/core.hpp>  
#include <opencv2/highgui/highgui.hpp> 
#include <opencv2/imgproc/imgproc.hpp>  // Gaussian Blur
#include <opencv2/ml/ml.hpp>
#include <opencv2/contrib/contrib.hpp>


using namespace cv;
using namespace std;




Scalar getMSSIM(char * imagePatha, char * imagePathb);


Scalar getMSSIM(char * imagePatha, char * imagePathb)
{
Mat i1 = imread(imagePatha);
Mat i2 = imread(imagePathb);
const double C1 = 6.5025, C2 = 58.5225;
int d = CV_32F;
Mat I1, I2;
i1.convertTo(I1, d);
i2.convertTo(I2, d);
Mat I2_2 = I2.mul(I2);
Mat I1_2 = I1.mul(I1);
Mat I1_I2 = I1.mul(I2);
Mat mu1, mu2;
GaussianBlur(I1, mu1, Size(11, 11), 1.5);
GaussianBlur(I2, mu2, Size(11, 11), 1.5);
Mat mu1_2 = mu1.mul(mu1);
Mat mu2_2 = mu2.mul(mu2);
Mat mu1_mu2 = mu1.mul(mu2);
Mat sigma1_2, sigma2_2, sigma12;
GaussianBlur(I1_2, sigma1_2, Size(11, 11), 1.5);
sigma1_2 -= mu1_2;
GaussianBlur(I2_2, sigma2_2, Size(11, 11), 1.5);
sigma12 -= mu1_mu2;
Mat t1, t2, t3;
t1 = 2 * mu1_mu2 + C1;
t2 = 2 * sigma12 + C2;
t3 = t1.mul(t2);
t1 = mu1_2 + mu2_2 + C1;
t2 = sigma1_2 + sigma2_2 + C2;
t1 = t1.mul(t2);
Mat ssim_map;
divide(t3, t1, ssim_map);
Scalar mssim = mean(ssim_map);
return mssim;
}

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