2013-04-28 114 views

回答

5

我不知道你以前使用过,但你可以使用下面的代码来计算改变图像的PSNR:

I = imread('original.jpg'); 
Ihat = imread('changed.jpg'); 

% Read the dimensions of the image. 
[rows columns ~] = size(I); 

% Calculate mean square error of R, G, B. 
mseRImage = (double(I(:,:,1)) - double(Ihat(:,:,1))) .^ 2; 
mseGImage = (double(I(:,:,2)) - double(Ihat(:,:,2))) .^ 2; 
mseBImage = (double(I(:,:,3)) - double(Ihat(:,:,3))) .^ 2; 

mseR = sum(sum(mseRImage))/(rows * columns); 
mseG = sum(sum(mseGImage))/(rows * columns); 
mseB = sum(sum(mseBImage))/(rows * columns); 

% Average mean square error of R, G, B. 
mse = (mseR + mseG + mseB)/3; 

% Calculate PSNR (Peak Signal to noise ratio). 
PSNR_Value = 10 * log10(255^2/mse); 
+0

为什么你需要在mseR,mseG和mseB公式中两次写入总和? – 2017-08-24 12:38:45

4

这里是一个矢量实现:

mse = mean(mean((im2double(I) - im2double(K)).^2, 1), 2); 
psnr = 10 * log10(1 ./ mean(mse,3)); 

它应该工作用于整数和浮点图像,包括灰度和彩色图像。

我使用以下PSNR定义:

mse

psnr