Image Normalization in the range 0 to 1
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Sapam Jaya
am 12 Dez. 2013
Kommentiert: DGM
am 13 Feb. 2023
How to normalize an image in the range 0 to 1?
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Image Analyst
am 12 Dez. 2013
Use mat2gray() or im2double(). Hopefully you have the image processing Toolbox.
normImage = mat2gray(yourImage);
normImage = im2double(yourImage);
Also look at stretchlim() and imadjust().
10 Kommentare
Image Analyst
am 23 Sep. 2021
If you really want them to have fractional values between 0 and 1, that's not a standard image format so you'll just have to save them with
save('myFile.mat', 'yourImageVariable');
to save them in a .mat file.
Weitere Antworten (3)
mutant
am 6 Okt. 2019
Old question but as of R2017b, rescale does exactly this.
B = rescale(A); % Normalizes image (0 to 1, by default)
You can even use this to scale to uint8, for example:
B = rescale(A,0,255); % Normalizes image to [0 255]
Documentation here:
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Azzi Abdelmalek
am 12 Dez. 2013
Bearbeitet: Azzi Abdelmalek
am 12 Dez. 2013
If im is your image
im=(im-min(im(:)))/(max(im(:))-min(im(:)))
1 Kommentar
Jos (10584)
am 12 Dez. 2013
I suggest to do this in two steps to avoid the calculation of MIN twice ...
IM = IM - min(IM(:)) ;
IM = IM / max(IM(:)) ;
Sajid Khan
am 6 Feb. 2014
Bearbeitet: DGM
am 13 Feb. 2023
function image_normalized = imnormalize( image_orig, min_norm, max_norm)
val_max = max(image_orig(:));
val_min = min(image_orig(:));
range = val_max - val_min;
image_normalized = (image_orig - val_min) ./ range; % Then scale to [x,y] via:
range2 = max_norm - min_norm;
image_normalized = (image_normalized*range2) + min_norm;
end
In this function, you can set min_norm = 0 and max_norm = 1 to normalize image to a scale of 0 to 1. If you have any other questions to ask, then you are welcome. I always use this function for normalization purpose. It even works if you have to increase the scale length.
2 Kommentare
Image Analyst
am 6 Feb. 2014
Your function basically does the same thing as the built in function mat2gray().
DGM
am 13 Feb. 2023
Rather, mat2gray() only allows the specification of the input levels, assuming the output levels are [0 1]. Sajid's function allows specification of the output levels, while using image extrema as the input levels.
So in that sense, it's more like rescale(), same syntax and everything.
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