Introduction: Decoding Secret Messages From Space!

About: Every now and then I come up with a unique idea. And then I find someone else has already thought of it . . . which is AWESOME! Who knew there were so many kindred spirits on the web! YOU GO all o' us!
This instructable shows my attempts at decoding secret messages from space . . . in the form of Fourier transformations of supercluster photos. Lemme explain.

I was reading through my Digital Image Processing book (2nd edition) about something called Fourier transforms. Without explaining the math, suffice it to say that any 2d image can be transformed into a mathematical representation called the Fourier domain. When you do a Fourier transform on a normal image, you get what looks like a cluster of stars. So me being me, I thought, what do you get if you do a Fourier transform on a picture of a cluster of stars? SECRET MESSAGES FROM SPACE!?

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Resources:
1. Image editing software that is capable of Fourier transformation (I'm sure there's a free astronomy tool out there SOMEWHERE)
2. Photos of objects in space (like nebulae)

Step 1: Find a Good Candidate Photo

First you must find a likely source of alien messages from space. Find a supercluster photo with a bright spot in the very center, crop or resize it to 512x512 pixels. Many Messier objects are good candidates.

Step 2: Inversely Transform the Image From Fourier Space

Perform an inverse Fourier transform (I used a shake plugin from pixelmaina), using the same image as both the real and mathematical imaginary (square root of -1) portion of the Fourier transform

Step 3: Re-Center the Image and Decode the Message

Center, Scroll (in Shake), or Offset (Filter>Other>Offset in Photoshop) the resulting image so that the brightest part is in the center. Now interpret the resulting image. This one reminds me of a planet with 50 moons and a race of sentient dog-beings.

Step 4: Areas of Future Research!

Well, obviously the signal to noise ratio is low, and a diagram of these space nebula would be more appropriate to Fourier transform than an actual photo.