How to separate RGB values of an image.
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Niranjan
am 1 Feb. 2011
Bearbeitet: Sailesh Sidhwani
am 3 Sep. 2020
We know that each pixel i in the input image I has rgb colors. My question is how to store them in a 3-vector Ii. Each color is being represented using a 64-bit floating-point number scaled to between 0 and 1.
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Jim Dowd
am 1 Feb. 2011
Sean de has told you how to get each plane, but it sounds like you want some kind of vector. I am not sure what you mean by a 3 vector, but here are a couple of guesses.
If you want 3 vectors:
R = reshape(I(:,:,1),[],1);
G = reshape(I(:,:,2),[],1);
B = reshape(I(:,:,3),[],1);
Now if you want them all together in a 3 column vector:
V3 = reshape(A(:),[],3) % R is first col, G is second col, B is third.
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Vespi
am 6 Mär. 2016
I extracted RGB values of my image using this code. I now have a .txt file with 3 columns. I was wondering how MatLab reads the image so that I can assign the pixel number corresponding to each RGB value in my .txt file.
Walter Roberson
am 6 Mär. 2016
MATLAB goes "down columns" in constructing the above. So if there were, for example, 5 rows of pixels in the image, the order in the file would be
(1,1)
(2,1)
(3,1)
(4,1)
(5,1)
(1,2)
(2,2)
(3,2)
(4,2)
(5,2)
(1,3)
(2,3)
...
Weitere Antworten (3)
Sailesh Sidhwani
am 25 Okt. 2018
Bearbeitet: Sailesh Sidhwani
am 3 Sep. 2020
Starting R2018b, Image Processing Toolbox has a new function "imsplit" which does exactly this: https://www.mathworks.com/help/images/ref/imsplit.html
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Sean de Wolski
am 1 Feb. 2011
Rchannel = I(:,:,1);
Gchannel = I(:,:,2);
Bchannel = I(:,:,3);
2 Kommentare
Walter Roberson
am 25 Okt. 2018
It is by definition: MATLAB interprets the first pane of the third dimension as being red values, the second pane of the third dimension as being green values, the third pane of the third dimension as being blue values.
That particular ordering is arbitrary: there is no reason why it could not have been Green, Red, Blue for example, which would have made some sense in terms of the sensitivity of the human eye to brightness in daylight. Or it could have been Blue that was first, reflecting the fact that the human eye is most sensitive to contrast in the blues. But for whatever reason, RGB was the order standardized on.
Sean de Wolski
am 1 Feb. 2011
You could also do it so you have a cell array with each index being a 3x1 vector, perhaps:
I2 = cellfun(@squeeze,num2cell(I,3),'uni',false);
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