http://imagej.273.s1.nabble.com/FFT-Power-Spectrum-Question-RGB-vs-8-bit-stack-tp5004177p5004183.html
Jack - to form the modulus image of the FT sum of the RGB channels, try Sum = sqrt(R^2 + G^2 + B^2)
> Hi Herbie,
>
> Yeah, I thought that Imagej would turn the image from RGB to 8 bit gray
> before running the FFT on it, but apparently not. The attached image shows
> running FFT on the RGB image, on the RGB image after converting to 8 bit
> gray and on the sum of the R, G, B slices divided by three respectively.
>
> The Raw Power Spectrum is not very helpful (a single dot with scaling, or
> mostly washed out without). Image conversion options are at default, which
> means that the weighted RGB box is unchecked.
>
> The FFT run directly on the RGB image still looks quite different from the
> others. Any other ideas?
>
> Thanks for your help!
>
> Jack
>
>
> On Sat, Jul 27, 2013 at 5:04 PM, Herbie <
[hidden email]> wrote:
>
>> Good day Jack,
>>
>> the differences may appear big in the display but please note that the
>> Fourier-spectral values are scaled according to the logarithm which
>> emphasizes the small values. If you don't want logarithmic spectra, then
>> check the "Raw power spectrum" option.
>>
>> I guess that IJ is creating a gray-value image before Fourier-transforming
>> the RGB-image and it does this according to the choice made under
>> "Conversion Options". Most probably you have "Weighted RGB Conversion"
>> checked.
>>
>> HTH
>>
>> Herbie
>>
>>
>> On 27.07.13 16:10, Jack Hogan wrote:
>>
>>> Hello folks,
>>>
>>> Can any of you Imagej experts illuminate a noob as to why the FFT Power
>>> Spectra of two image types of the exact same image look so different?
>>> Specifically, referring to the attached image, the top row is the 8bit
>>> RGB
>>> rendition of a raw file with minimal demosaicing and its FFT. The bottom
>>> row is the same RGB 8 bit rendition but after having been 'stacked'
>>> through
>>> Image/Color/MakeComposite and an FFT generated for each color slice.
>>>
>>> How does Imagej's FFT algorithm combine the separate RGB channels to come
>>> up with its power spectrum? And why is it so different from the individual
>>> channels'?
>>>
>>> Thank you for your help.
>>>
>>> Jack
>>>
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>>>
>>>
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http://imagej.nih.gov/ij/list.html> <FFT RGB vs 8b vs R+G+B_3.jpg>