Prashant Kumar answered . 2024-04-26 23:47:00

[img, ~, transp] = imread('https://upload.wikimedia.org/wikipedia/commons/a/ac/NewTux.png');
alphadata = im2double(transp);

subplot(1,2,1)
h = imshow(img);
h.AlphaData = alphadata;

Alpha data is not necessarily just 0 (transparent) or maximum (completely opaque) so you need to decide whether for histogram equalization you want anything non-zero to be included, or anything non-maximum to be excluded.

mask = alphadata >= 0.5;

And now you can

masknd = repmat(mask,[1 1 size(img,3)]);
masked_pixels = img(masknd);    %extract into vector
masked_pixels = reshape(masked_pixels, [nnz(mask), ones(1,ndims(img)-2), size(img,3)]); %reshape to rgb if needed

equalized_masked = histeq(masked_pixels);
eq_img = img;
eq_img(masknd) = equalized_masked;

subplot(1,2,2)
h = imshow(eq_img);
h.AlphaData = alphadata;

I suggest you consider using double(mask) as the AlphaData for imshow purposes. In particular, look at the shadows underneath the penguin: they are semi-transparent with alpha less than 1/2 so they are not included in equalization, but they do show up when using alphadata as the transparency mask -- which is done to be consistent with the transparency data stored in the original image.

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