Hi Neki! Once again, great work.

It help me to try again with Image Analyzer and, after a few tries, I think I got a good match:

**The left** is Raj PICT0016 proceed as usual: 256*256 square of blue sky----->convert to grayscale----->highpass filter both direction radius 3px------>Fourier transform----->Complex map representation square root method with color range 0>x>0.4

**The right** is the blue sky portion of my image test proceed like this:

1- Add Noise intensity 20 and saturation 200

2- Save as JPEG 70% (!!)

Then, with Image Analyzer, the usual process:

Convert to grayscale----->highpass filter both direction radius 3px------>Fourier transform----->Complex map representation square root method with color range 0>x>0.4.

NOTE: I haven't add any Gaussian blur, since the differences between the results of various radius test are not very obvious, however maybe you can try it, using the same process as mine?

We can try to refine this, maybe with a complete study including split color plane (RGB) and recombine fft.

What could be the conclusion of these results?

1- There's (maybe) a slight addition of Gaussian blur, need to be confirmed.

2- Jtp was wrong when he said that jpeg compression doesn't affect the fft.

3-

**It's a combination of noise and jpeg compression artifact** that gives this fft shape of Raj's PICT0016 picture.

4-

**The noise added is consequen**t (Intensity 20 and color saturation +/-200). The question is why the hell Raj or his brother-in-law added this noise? Unless there is an automatic process that can add it....

5- The Jpeg compression is somewhere around 70-80%.

Another consequence of this is that,

**but we need to verify the fft in full colors**, we can say that Raj effectively used a Minolta DimageX, but that the fft was degraded by addition of noise and by saving the picture in jpeg at 70-80%.