OpenCv中图像PSNR和SSIM的计算

double psnr(Mat &I1, Mat &I2){
	Mat s1;
	absdiff(I1, I2, s1);
	s1.convertTo(s1, CV_32F);//转换为32位的float类型，8位不能计算平方
	s1 = s1.mul(s1);
	Scalar s = sum(s1);  //计算每个通道的和
	double sse = s.val[0] + s.val[1] + s.val[2];
	if( sse <= 1e-10) // for small values return zero
		return 0;
	else
	{
		double mse = sse / (double)(I1.channels() * I1.total()); //  sse/(w*h*3)
		double psnr = 10.0 * log10((255*255)/mse);
		return psnr;
	}
	
	
	

}
double ssim(Mat &i1, Mat & i2){
	const double C1 = 6.5025, C2 = 58.5225;
	int d = CV_32F;
	Mat I1, I2;
	i1.convertTo(I1, d);
	i2.convertTo(I2, d);
	Mat I1_2 = I1.mul(I1);
	Mat I2_2 = I2.mul(I2);
	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, sigam2_2, sigam12;
	GaussianBlur(I1_2, sigma1_2, Size(11, 11), 1.5);
	sigma1_2 -= mu1_2;

	GaussianBlur(I2_2, sigam2_2, Size(11, 11), 1.5);
	sigam2_2 -= mu2_2;

	GaussianBlur(I1_I2, sigam12, Size(11, 11), 1.5);
	sigam12 -= mu1_mu2;
	Mat t1, t2, t3;
	t1 = 2 * mu1_mu2 + C1;
	t2 = 2 * sigam12 + C2;
	t3 = t1.mul(t2);

	t1 = mu1_2 + mu2_2 + C1;
	t2 = sigma1_2 + sigam2_2 + C2;
	t1 = t1.mul(t2);

	Mat ssim_map;
	divide(t3, t1, ssim_map);
	Scalar mssim = mean(ssim_map);

	double ssim = (mssim.val[0] + mssim.val[1] + mssim.val[2]) /3;
	return ssim;
}