Here is a Sample Program to reproduce the same!
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
#include <iostream>
using namespace cv;
using namespace std;
bool AddGaussianNoise(const Mat mSrc, Mat &mDst,double Mean=0.0, double StdDev=10.0)
{
if(mSrc.empty())
{
cout<<"[Error]! Input Image Empty!";
return 0;
}
Mat mSrc_16SC;
Mat mGaussian_noise = Mat(mSrc.size(),CV_16SC3);
randn(mGaussian_noise,Scalar::all(Mean), Scalar::all(StdDev));
mSrc.convertTo(mSrc_16SC,CV_16SC3);
addWeighted(mSrc_16SC, 1.0, mGaussian_noise, 1.0, 0.0, mSrc_16SC);
mSrc_16SC.convertTo(mDst,mSrc.type());
return true;
}
double GetPSNR(const Mat& I1, const Mat& I2,double &MSE)
{
Mat s1;
absdiff(I1, I2, s1); // |I1 - I2|
s1.convertTo(s1, CV_32F); // cannot make a square on 8 bits
s1 = s1.mul(s1); // |I1 - I2|^2
Scalar s = sum(s1); // sum elements per channel
double sse = s.val[0] + s.val[1] + s.val[2]; // sum channels
if( sse <= 1e-10) // for small values return zero
return 0;
else
{
double mse =sse /(double)(I1.channels() * I1.total());
MSE= mse;
double psnr = 10.0*log10((255*255)/mse);
return psnr;
}
}
int main(int argc, const char* argv[])
{
Mat mScene= imread("input.png",1);
imshow("Source Image",mScene);
Mat mNoise(mScene.size(),mScene.type());
double Mean=0.0,StdDev=20.0;
AddGaussianNoise(mScene,mNoise,Mean,StdDev);
imshow("mNoise",mNoise);
double PSNR=0.0,MSE=0.0;
PSNR= GetPSNR(mScene,mNoise,MSE);
cout<< "PSNR : "<<PSNR<<" \n MSE :"<<MSE <<"\n";
waitKey();
return 0;
}
I suspect you are computing the MSE in the wrong way! Can you add your code?
//For gray level image
for(int y = 0; y < width; y++){ for(int x = 0; x < height;x++){