# I have a question in image processing, this code shows how to add noise to the image and then retrieve it again ... The problem when retrieving the image error occurs and show the image that was retrieved in white

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Ahmed Grera on 2 Sep 2017
Commented: Image Analyst on 3 Sep 2017
img = imread( ('eight.tif') ); % read image, use gray-level images here.
A = imnoise(img,'Gaussian',0,1);
IMG = fft2( img ); % Fourier of img
sz = size( img );
G = fspecial('gaussian' ,[5,5]); % create a filter with std sigma same size as img
%# Filter it
h = imfilter(A,G,'same');
H = fft2( h ); % Fourier of filter
F = IMG.*H; % filter in Fourier space
f = ifft2( F ); % back to spatial domain.
figure, imagesc(f);title('Gaussian filter in Frequency Domain')
figure,imshow(img),title('Original Image');
figure,imshow(A),title('Noisy Image');
imshow(f)
% Calculate MSE, mean square error.
img =im2double(img);
f =im2double(f);
[M N] = size(img);
error0 = img - f;
Mean_Square_Error = sum(sum(error0 .* error0)) / (M * N)

Walter Roberson on 2 Sep 2017
The result of
img = imread( ('eight.tif') ); % read image, use gray-level images here.
is almost certainly going to be one of the integer data types.
The result of
f = ifft2( F ); % back to spatial domain.
is going to be double precision.
>> min(f(:)),max(f(:))
ans =
2241610061
ans =
2319637632
... that is not even in the same range.

Image Analyst on 3 Sep 2017
Try this, using [] to scale the image before display:
imshow(f, []);
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Image Analyst on 3 Sep 2017
Who told you that nonsense?