Color normalization algorithm under various lighting conditions

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LANG Wu
LANG Wu 2020-4-24
评论： LANG Wu 2020-4-28
I am trying to take pictures using cellphones under various lighting conditions which would cause color distortions. Hence some kind of white balance algorithm is needed to correct the lighting of those photos so we get the standardized color. This can be commonly done if you have a "gray card" which many photographers use to tell their cameras what is the true white color under any light. With the "gray card", a person can take a picture with a standard color item by the side. With the item's color as a reference, we hope we can standardize the picture's color. We are doing this for an excellent color normalization.
Does anybody know any readily available algorithms (or something we can modify) for the above purpose? I really appreciate it if you can offer any suggestions.
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LANG Wu
LANG Wu 2020-4-24
That's hard to say. But maybe we can make it in the top right or left. Or we can take two pictures, one for the object, the other for the identificator.

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Image Analyst
Image Analyst 2020-4-24
There is a whole family of functions to do this. In the Image Processing Toolbox, check out illumgray(), illumpca(), illumwhite(), and chromadapt().
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Image Analyst
Image Analyst 2020-4-28
Actually you can do steps 1 and 2 using rgb2gray()
grayImage = rgb2gray(rgbImage);
mask = grayImage > 180; % or whatever gray level your white card is.
% Extract the individual red, green, and blue color channels.
redChannel = rgbImage(:, :, 1);
greenChannel = rgbImage(:, :, 2);
blueChannel = rgbImage(:, :, 3);
meanR = mean(redChannel(mask))
meanG = mean(greenChannel(mask))
meanB = mean(blueChannel(mask))
maxR = max(redChannel(mask))
maxG = max(greenChannel(mask))
maxB = max(blueChannel(mask))
deltaR = uint8(maxR - meanR)
deltaG = uint8(maxG - meanG)
deltaB = uint8(maxB - meanB)
newR = redChannel + deltaR;
newG = greenChannel + deltaG;
newB = blueChannel + deltaB;
newRGB = cat(3, newR, newG, newB);
imshow(newRGB);
See attached color standardization and calibration tutorial from my course I teach.
LANG Wu
LANG Wu 2020-4-28
Thanks again. Actually what I want to do is select the white card area, get its illumination and tell the algorithm this is 'white', and then normalize the image color considering the white card's illumination as standard. I don't see how you define the 'white' color in your code. Why do you choose 'grayscale>180" and what does 'delta' mean?

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darova
darova 2020-4-25
Try this trick
I = imread('peppers.png');
imshow(I)
p = round(ginput(1));
for i = 1:3
I(:,:,i) = I(:,:,i) + (255 - I(p(2),p(1),i));
end
imshow(I)

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