Question

I have the following code, which I am trying to normalize my images after filtering but the problem is that as soon as it get to line 5, it change everyting to 0 and it returns me black images. any idea ?

 for i=1:10     
     temp_imag = imag_test1{i}(:,:);
     t_max = max(max(temp_imag));
     t_min = min(min(temp_imag));
     temp_imag = (temp_imag-t_min).*double(((new_max-new_min)/(t_max-t_min)))+double(new_min);
     imag_test1{i}(:,:) = temp_imag;
 end

Answer 1

You don’t tell which values new_max and new_min get, but anyway if every after line 5 (temp_imag = (temp_imag-t_min).*double(((new_max-new_min)/(t_max-t_min)))+double(new_min);
) everything becomes zero, there are a few possibilities:

1. imga_test{i} (1 <= i <= 10) are all zeros and new_min is also zero. Have you checked the value of imga_test that they are not all zeros and that they vary? You can create example data for imga_test eg. by using rand or randi. If random data gives you non-zeros, the problem is in imga_test.

2. new_max-new_min is zero, which means that new_max and new_min have same value. Have you tried changing values for new_max and new_min and changing their difference? If changing the values of new_max, new_min or both gives you non-zeros, the problem is in new_max and new_min.

3. By using solve to solve the equation eg. for new_min:

   solve('temp_imag = (temp_imag-t_min)*(((new_max-new_min)/(t_max-t_min)))+(new_min)', 'new_min'):

   ans =
(new_max*t_min - new_max*temp_imag - t_min*temp_imag + t_max*temp_imag)/(t_max - temp_imag)

This third case is very improbable.