Different Pixel Values in MATLAB and C++ with OpenCV

I see there are similar questions to this but don't quiet answer what I am asking so here is my question.

In C++ with OpenCV I run the code I will provide below and it returns an average pixel value of 6.32. However, when I open the image and use the mean function in MATLAB it returns an average pixel intensity of approximately 6.92ish. As you can see I convert the OpenCV values to double to try to ease this issue and have found that openCV loads the image as a set of integers whereas MATLAB loads the image as decimal values that are approximately but not quite the same obviously as the integers. So my question is, being new to coding, which is correct? I'm assuming MATLAB is returning more accurate values and if that is the case I would like to know if there is a way to load the images in the same fashion to avoid the discrepancy.

Thank you, Code below

    Mat img = imread("Cells2.tif");
cv::cvtColor(img, img, CV_BGR2GRAY);
cv::imshow("stuff",img);
Mat dst;
if(img.channels() == 3)
{
    img.convertTo(dst, CV_64FC1);
}
else if (img.channels() == 1) 
{
    img.convertTo(dst, CV_64FC1);
}
cv::imshow("output",dst/255);
int NumPixels = img.total();


double avg;
double c = 0; 
double std;
    for(int y = 0; y < dst.cols; y++)
    { 

        for(int x = 0; x < dst.rows; x++)
        {
            c+=dst.at<double>(x,y)*255;
        }
    }

avg = c/NumPixels;
cout << "asfa = " << c << endl;
double deviation;

double var;
double z = 0;
double q;
    //for(int a = 0; a<= img.cols; a++)
for(int y = 0; y< dst.cols; y++)
    {
        //for(int b = 0; b<= dst.rows; b++)
        for(int x = 0; x< dst.rows; x++)
        {
            q=dst.at<double>(x,y);

            deviation = q - avg;
            z = z + pow(deviation,2);
            //cout << "q = " << q << endl;
        }

    }

var = z/(NumPixels);
std = sqrt(var);
cv::Scalar avgPixel = cv::mean(dst);

cout << "Avg Value = " << avg << endl;
cout << "StdDev = " << std << endl;
cout << "AvgPixel =" << avgPixel;

cvWaitKey(0);
return 0;

}

According to your comment, the image seems to be stored with a 16-bit depth. MATLAB loads the TIFF image as is, while by default OpenCV will load images as 8-bit. This might explain the difference in precision that you are seeing.

Use the following to open the image in OpenCV:

cv::Mat img = cv::imread("file.tif", cv::IMREAD_ANYDEPTH|cv::IMREAD_ANYCOLOR);

In MATLAB, it's simply:

img = imread('file.tif');

Next you need to be aware of the data type you are working with. In OpenCV its CV_16U, in MATLAB its uint16 . Therefore you need to convert types accordingly.

For example, in MATLAB:

img2 = double(img) ./ double(intmax('uint16'));

would convert it to a double image with values in the range [0,1]

加载图像时，必须在两种环境（MATLAB和OpenCV）中使用类似的方法，以避免可能在任一环境中默认进行的转换。

long long total = 0;
long long divisor = image.width * image.height;
for(int x = 0; x < image.width; ++x)
{
    for(int y = 0; x < image.height; ++x)
    {
        total += image.at(x,y).color;
    }
}
double avg = total / divisor;
std::cout << "Average color value: " << avg << std::endl;

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