Why image values are different in Matlab and OpenCV? - image

Question

I have an original image:
I then read it, create a PSF, and blur it in Matlab:
lenawords1=imread('lenawords.bmp');
%create PSF
sigma=6;
PSFgauss=fspecial('gaussian', 8*sigma+1, sigma);
%blur it
lenablur1=imfilter(lenawords1, PSFgauss, 'conv');
lenablurgray1=mat2gray(lenablur1);
PSFgaussgray = mat2gray(PSFgauss);
and I saved the blurred image:
imwrite(lenablurgray1, 'lenablur.bmp');
When I display some values in it, I get
disp(lenablurgray1(91:93, 71:75))
0.5556 0.5778 0.6000 0.6222 0.6444
0.6000 0.6444 0.6667 0.6889 0.6889
0.6444 0.6889 0.7111 0.7333 0.7333
I then open that blurred image in OpenCV and display its values at the same indices:
Mat img = imread("lenablur.bmp");
for (int r = 91; r < 94; r++) {
for (int c = 71; c < 76; c++) {
cout << img.at<double>(r, c) << " ";
}
cout << endl;
}
cout << endl;
The result I get doesn't match the values above:
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
Why is this?
EDIT: img.at<unsigned int>(r, c) gives
1903260029 1533437542 ...
2004318088 ...
....
If I save the blurred image as a png file:
imwrite(lenablurgray1, 'lenablur.png');
Then when I read it in OpenCV:
Mat img = imread("lenablur.png");
img.convertTo(img, CV_64F);
then img.at<double>(r, c) gives
17 11 11 11 6
17 11 11 11 6
17 11 11 11 11
which still doesn't match the values from Matlab
EDIT2: I now see the values are wrong for the kernel. In Matlab, I get
imwrite(PSFgaussgray, 'PSFgauss.bmp');
disp(PSFgaussgray(7:9, 7:9)*256)
.0316 .0513 .0812
.0513 ...
...
whereas in OpenCV:
Mat kernel = imread("PSFgauss.bmp");
cvtColor(kernel, kernel, cv::COLOR_BGR2GRAY);
kernel.convertTo(kernel, CV_64F);
for (int r = 6; r < 9 ; r++) {
for (int c = 6; c < 9; c++) {
cout << kernel.at<double>(r, c) << " ";
}
cout << endl;
}
cout << endl;
The result I get doesn't match the values above:
0 0 0
0 0 0
0 0 0

Answer 1

To understand the discrepancy you see you need to know how MATLAB saves images to a BMP or PNG file, and how OpenCV reads it.
MATLAB assumes, if the image is of type double as is this case, that its intensity range is [0,1]. That is, pixel values below 0 and above 1 are not expected. Such images are multiplied by 255 and converted to 8-bit integers (which have a range of [0,255]) when saved to a file.
Thus, if
>> disp(lenablurgray1(91:93, 71:75))
0.5556 0.5778 0.6000 0.6222 0.6444
0.6000 0.6444 0.6667 0.6889 0.6889
0.6444 0.6889 0.7111 0.7333 0.7333
what is saved is
>> uint8( lenablurgray1(91:93, 71:75) * 255 )
142 147 153 159 164
153 164 170 176 176
164 176 181 187 187
Next, OpenCV will read this file as RGB (or rather BGR, OpenCV's awkward color order) and as 8-bit unsigned integer (CV_8U). To display these data, either extract one of the color channels, or convert to gray value using
cvtColor(img, img, cv::COLOR_BGR2GRAY);
Then, read the 8-bit unsigned values with
img.at<uchar>(r, c)
If you read them with img.at<double>(), groups of 8 consecutive pixels will be regarded as a single pixel value (a double has 8 bytes).
Next, remember that MATLAB's indexing starts at 1, whereas OpenCV's starts at 0. So your loop should look like this:
for (int r = 90; r < 93; r++) { // matches MATLAB's 91:93 indexing
for (int c = 70; c < 75; c++) { // matches MATLAB's 71:75 indexing
cout << (int)img.at<uchar>(r, c) << " ";
}
cout << '\n';
}
cout << '\n';
Finally, in the case of your kernel, note that its values, when multiplied by 255 are still much smaller than unity: .0316 .0513 .0812. These values will be written as 0 to the BMP or PNG file. If you want to save these values, you need to scale the kernel so its maximum value is 1:
PSFgauss = PSFgauss / max(PSFgauss(:));
imwrite(PSFgauss, 'PSFgauss.bmp');
(Note that this kernel is already a grey-value image, you don't need to use mat2gray on it.)